WO2022240186A1 - Procédé de correction de distorsion d'image et dispositif électronique associé - Google Patents

Procédé de correction de distorsion d'image et dispositif électronique associé Download PDF

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Publication number
WO2022240186A1
WO2022240186A1 PCT/KR2022/006737 KR2022006737W WO2022240186A1 WO 2022240186 A1 WO2022240186 A1 WO 2022240186A1 KR 2022006737 W KR2022006737 W KR 2022006737W WO 2022240186 A1 WO2022240186 A1 WO 2022240186A1
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WIPO (PCT)
Prior art keywords
processor
electronic device
lattice
image
line
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PCT/KR2022/006737
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English (en)
Korean (ko)
Inventor
신대규
문승민
임광용
Original Assignee
삼성전자 주식회사
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Publication of WO2022240186A1 publication Critical patent/WO2022240186A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/80—Geometric correction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/18—Image warping, e.g. rearranging pixels individually
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/57—Mechanical or electrical details of cameras or camera modules specially adapted for being embedded in other devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/61—Control of cameras or camera modules based on recognised objects
    • H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • H04N23/81—Camera processing pipelines; Components thereof for suppressing or minimising disturbance in the image signal generation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
    • H04N25/61—Noise processing, e.g. detecting, correcting, reducing or removing noise the noise originating only from the lens unit, e.g. flare, shading, vignetting or "cos4"

Definitions

  • Embodiments disclosed in this document relate to an electronic device and method for correcting distortion of an image.
  • a digital camera-level field of view is required for a camera of the mobile terminal. Therefore, cameras with various angles of view are applied to mobile terminals, and in particular, wide-angle cameras (eg, ultra wide) can display a wide area on the display of mobile terminals.
  • a stereographic projection method is a method used to correct an object by changing the angle of view in an image distorted by lens characteristics.
  • correction in the form of extending the image periphery to reduce distortion of the line can correct the line, but causes a problem of intensifying distortion of an object other than the line.
  • Various embodiments of the present disclosure provide a method capable of identifying characteristics of each region of an image and performing at least one of line correction, face correction, and/or object correction for each region based on the identified characteristics.
  • an electronic device includes an image sensor, a display, and at least one processor operatively connected to the image sensor and the display, and the at least one processor acquires an image frame through the image sensor to obtain an image. Dividing the frame into a plurality of lattice areas, detecting at least one element among at least one object or line component in the acquired image frame, and analyzing the lattice area including the detected at least one element, thereby forming a plurality of lattice areas.
  • An area to be subjected to line distortion correction is determined, and based on the determined area, a first lattice area among a plurality of lattice areas performs line distortion correction based on a first weight, and a second lattice area among the plurality of lattice areas is determined based on the determined area. may perform line distortion correction based on the second weight, and display an image frame on which distortion correction is performed on a display.
  • An operating method of an electronic device includes obtaining an image frame through an image sensor, dividing the image frame into a plurality of lattice areas, and selecting at least one element among at least one object or line component in the obtained image frame. Detecting, analyzing a lattice area including at least one detected element, and determining an area to perform line distortion correction among a plurality of lattice areas, based on the determined area, a first lattice area among the plurality of lattice areas An operation of performing line distortion correction on a region based on a first weight, and performing line distortion correction on a second grid region among a plurality of grid regions based on a second weight, and displaying an image frame on which distortion correction is performed on a display. action may be included.
  • power consumption may be minimized by reducing an amount of computation related to correction.
  • distortion is minimized even in a wide-angle shooting environment, so that high-quality photos can be provided to the user.
  • FIG. 1 is a diagram illustrating structures of an electronic device and a camera module according to an embodiment.
  • FIG. 2 illustrates a hardware configuration of an electronic device according to an embodiment.
  • FIG 3 illustrates a process for correcting image distortion in an electronic device according to an embodiment.
  • FIG. 4 illustrates a process of performing line correction on an image obtained by an electronic device according to an embodiment.
  • FIG 5 illustrates a process of performing object correction on an image acquired by an electronic device according to an embodiment.
  • FIG. 6 is a flowchart illustrating a process for correcting a distorted image in an electronic device according to an embodiment.
  • FIG. 7 is a diagram illustrating that an electronic device divides and analyzes an input image into grid areas according to an exemplary embodiment.
  • FIG. 8 illustrates a first image 700 acquired by an electronic device and a region obtained by cropping a part of the first image 700 according to an exemplary embodiment.
  • FIG. 9 illustrates matching of mismatched cell points generated in a process of performing warping in an electronic device according to an embodiment.
  • FIG. 10 is a block diagram of an electronic device in a network environment according to various embodiments.
  • FIG. 11 is a block diagram illustrating a camera module, according to various embodiments.
  • FIG. 1 is a diagram illustrating structures of an electronic device and a camera module according to an embodiment.
  • FIG. 1 is a diagram schematically illustrating an external appearance of an electronic device 100 equipped with a camera module 180 and a camera module 180 according to an exemplary embodiment.
  • FIG. 1 has been illustrated and described on the premise of a mobile device, in particular, a smart phone, it can be applied to an electronic device equipped with a camera among various electronic devices or mobile devices to those skilled in the art. will be clearly understood.
  • a display 110 may be disposed on a front surface of an electronic device 100 according to an embodiment.
  • the display 110 may occupy most of the front surface of the electronic device 100 .
  • a display 110 and a bezel 190 area surrounding at least some edges of the display 110 may be disposed on the front surface of the electronic device 100 .
  • the display 110 may include a flat area and a curved area extending from the flat area toward the side of the electronic device 100 .
  • the electronic device 100 shown in FIG. 1 is an example, and various embodiments are possible.
  • the display 110 of the electronic device 100 may include only a flat area without a curved area or may have a curved area only at one edge rather than both sides.
  • the curved area extends to the rear surface of the electronic device, so that the electronic device 100 may include an additional flat area.
  • the electronic device 100 may additionally include a speaker, a receiver, a front camera, a proximity sensor, a home key, and the like.
  • the rear cover 150 may be integrally provided with the main body of the electronic device.
  • the rear cover 150 may be separated from the main body of the electronic device 100 and may have a form in which a battery can be replaced.
  • the rear cover 150 may also be referred to as a battery cover or a rear cover.
  • a fingerprint sensor 171 for recognizing a user's fingerprint may be included in the first area 170 of the display 110 . Since the fingerprint sensor 171 is disposed on a lower layer of the display 110, it may not be recognized by the user or may be difficult to be recognized.
  • a sensor for additional user/biometric authentication may be disposed in a partial area of the display 110 .
  • a sensor for user/biometric authentication may be disposed in one area of the bezel 190 . For example, an IR sensor for iris authentication may be exposed through one area of the display 110 or through one area of the bezel 190 .
  • a front camera 161 may be disposed in the second region 160 of the front of the electronic device 100 .
  • the front camera 161 is shown as being exposed through one area of the display 110, but in another embodiment, the front camera 161 may be exposed through the bezel 190.
  • the electronic device 100 may include one or more front cameras 161 .
  • the electronic device 100 may include two front cameras such as a first front camera and a second front camera.
  • the first front camera and the second front camera may be cameras of the same type having the same specifications (eg, pixels), but the first front camera and the second front camera may be implemented as cameras having different specifications.
  • the electronic device 100 may support functions related to dual cameras (eg, 3D shooting, auto focus, etc.) through two front cameras. The above-mentioned description of the front camera may be equally or similarly applied to the rear camera of the electronic device 100 .
  • the electronic device 100 may additionally include various types of hardware or sensors 163 that assist shooting, such as a flash.
  • a distance sensor eg, a TOF sensor
  • the distance sensor may be applied to both a front camera and/or a rear camera.
  • the distance sensor may be disposed separately or included in the front camera and/or the rear camera.
  • At least one physical key may be disposed on a side surface of the electronic device 100 .
  • the first function key 151 for turning on/off the display 110 or turning on/off the power of the electronic device 100 may be disposed on the right edge of the electronic device 100 based on the front side.
  • the second function key 152 for controlling the volume or screen brightness of the electronic device 100 may be disposed at the left edge of the electronic device 100 based on the front surface.
  • additional buttons or keys may also be disposed on the front or rear of the electronic device 100.
  • a physical button or touch button mapped to a specific function may be disposed in a lower area of the front bezel 190 .
  • the electronic device 100 shown in FIG. 1 corresponds to one example and does not limit the shape of a device to which the technical ideas disclosed in this disclosure are applied.
  • a foldable electronic device capable of being folded horizontally or vertically a rollable electronic device capable of rolling, a tablet or a laptop may also be used according to the technical spirit of the present disclosure. this may apply.
  • the present technical concept may be applied even when the first camera and the second camera facing the same direction can be disposed to face different directions through rotation, folding, or deformation of the device.
  • an electronic device eg, electronic device 1001 of FIG. 10) 100 may include a camera module (eg, camera module 1080 of FIG. 10) 180.
  • the camera module 180 includes a lens assembly (eg, the lens assembly 1110 of FIG. 11) 111, a housing 113, an infrared cut filter 115, an image sensor (eg, the image of FIG. 11 ).
  • a sensor 1130) 120 and an image signal processor (eg, the image signal processor 1160 of FIG. 11) 130 may be included.
  • the lens assembly 111 may have different numbers, arrangements, and types of lenses according to the front camera and the rear camera.
  • the front camera and rear camera may have different characteristics (eg, focal length, maximum magnification, etc.).
  • the lens can be moved forward and backward along the optical axis, and can be operated so that a target object to be a subject can be clearly photographed by changing a focal length.
  • the camera module 180 may include a lens barrel for mounting at least one lens aligned on an optical axis and a housing 113 for mounting at least one coil surrounding the barrel around the optical axis.
  • the infrared cut filter 115 may be disposed on the upper surface of the image sensor 120 .
  • An image of the subject passing through the lens may be partially filtered by the infrared cut filter 115 and then detected by the image sensor 120 .
  • the image sensor 120 may be disposed on the upper surface of the printed circuit board.
  • the image sensor 120 may be electrically connected to the image signal processor 130 connected to the printed circuit board 140 through a connector.
  • a flexible printed circuit board (FPCB) or a cable may be used as the connector.
  • the image sensor 120 may be a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD) sensor.
  • CMOS complementary metal oxide semiconductor
  • CCD charged coupled device
  • a plurality of individual pixels are integrated in the image sensor 120, and each individual pixel may include a micro lens, a color filter, and a photodiode.
  • Each individual pixel can convert input light into an electrical signal as a kind of photodetector.
  • Photodetectors generally cannot detect the wavelength of the captured light by themselves and cannot determine color information.
  • the photodetector may include a photodiode.
  • light information of a subject incident through the lens assembly 111 may be converted into an electrical signal by the image sensor 120 and input to the image signal processor 130 .
  • the camera module 180 may be disposed on the front as well as the back of the electronic device 100 .
  • the electronic device 100 may include not only one camera module 180 but also multiple camera modules 180 to improve camera performance.
  • the electronic device 100 may further include a front camera 161 for video call or self-portrait.
  • the front camera 161 may support a relatively low number of pixels compared to the rear camera module.
  • the front camera may be relatively smaller than the rear camera module.
  • FIG. 2 illustrates a hardware configuration of an electronic device according to an embodiment.
  • the configuration described in FIG. 1 may be briefly described or omitted.
  • the electronic device 100 includes a camera module 180, a processor (eg, the processor 1020 of FIG. 10) 220, a display (eg, the display module 1060 of FIG. 10) ) 110 and a memory (eg, the memory 1030 of FIG. 10) 230.
  • a processor eg, the processor 1020 of FIG. 10
  • a display e.g, the display module 1060 of FIG. 10)
  • a memory eg, the memory 1030 of FIG. 10) 230.
  • descriptions of the same reference numerals as in FIG. 1 may be omitted.
  • the camera module 180 may include a lens assembly 111 , an image sensor 120 , a distance detection sensor 210 and an image signal processor 130 .
  • the electronic device 100 may further include additional components.
  • the electronic device 100 may further include at least one microphone for recording audio data.
  • the electronic device 100 may include at least one sensor for determining a direction in which the front or rear side of the electronic device 100 faces and/or attitude information of the electronic device 100 .
  • the at least one sensor may include an acceleration sensor, a gyro sensor, and the like. A detailed description of hardware included or may be included in the electronic device 100 of FIG. 2 is provided with reference to FIG. 11 .
  • the image sensor 120 may include a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD) sensor.
  • CMOS complementary metal oxide semiconductor
  • CCD charged coupled device
  • Light information of a subject incident through the lens assembly 111 may be converted into electrical signals by the image sensor 120 and input to the image signal processor 130 .
  • An infrared cut filter (hereinafter referred to as an IR cut filter) may be disposed on the upper surface of the image sensor 120, and an image of a subject passing through the lens is partially filtered by the IR cut filter, and then the image sensor 120 ) can be detected by
  • the image signal processor 130 and the image sensor 120 when the image signal processor 130 and the image sensor 120 are physically separated, there may be a sensor interface that meets the standard.
  • the image signal processor 130 may perform image processing on electrically converted image data.
  • a process in the image signal processor 130 may be divided into a pre-ISP (hereinafter referred to as pre-processing) and an ISP chain (hereinafter referred to as post-processing).
  • Image processing before the demosaicing process may mean pre-processing, and image processing after the demosaicing process may mean post-processing.
  • the preprocessing process may include 3A processing, lens shading correction, edge enhancement, dead pixel correction, and knee correction.
  • the 3A may include at least one of auto white balance (AWB), auto exposure (AE), and auto focusing (AF).
  • the post-processing process may include at least one of changing a sensor index value, changing a tuning parameter, and adjusting an aspect ratio.
  • the post-processing process may include processing image data output from the image sensor 120 or image data output from the scaler.
  • the image signal processor 130 may adjust contrast, sharpness, saturation, dithering, and the like of an image through a post-processing process.
  • the contrast, sharpness, and saturation adjustment procedures may be executed in the YUV color space, and the dithering procedure may be executed in the RGB (Red Green Blue) color space.
  • RGB Red Green Blue
  • Some of the pre-processing may be performed in the post-processing process, or some of the post-processing may be performed in the pre-processing process. Also, some of the pre-processing processes may overlap with some of the post-processing processes.
  • the display 110 may display content such as an execution screen of an application executed by the processor 220 or an image and/or video stored in the memory 230 on the display 110 .
  • the processor 220 may display image data acquired through the camera module 180 on the display 110 in real time.
  • the display 110 may be integrally implemented with the touch panel.
  • the display 110 may support a touch function, detect a user input such as a touch using a finger, and transmit the same to the processor 220 .
  • the display 110 may be connected to a display driver integrated circuit (DDIC) for driving the display 110, and the touch panel may be connected to a touch IC that detects touch coordinates and processes touch-related algorithms.
  • DDIC display driver integrated circuit
  • the display driving circuit and the touch IC may be integrally formed, and in another embodiment, the display driving circuit and the touch IC may be formed separately.
  • the display driving circuit and/or touch IC may be electrically connected to the processor 220 .
  • the processor 220 may execute/control various functions supported by the electronic device 100 .
  • the processor 220 may execute an application and control various types of hardware by executing codes written in a programming language stored in the memory 230 .
  • the processor 220 may execute an application that supports a photographing function stored in the memory 230 .
  • the processor 220 may execute the camera module 180 and set and support an appropriate shooting mode so that the camera module 180 may perform an operation intended by the user.
  • the memory 230 may store instructions executable by the processor 220 .
  • the memory 230 may be understood as a concept including a component for temporarily storing data, such as random access memory (RAM), and/or a component for permanently storing data, such as a solid state drive (SSD).
  • the processor 220 may implement a software module in the RAM space by calling instructions stored in the SSD.
  • the memory 230 may include various types, and an appropriate type may be selected according to the purpose of the device.
  • an application associated with the camera module 180 may be stored in the memory 230 .
  • a camera application may be stored in the memory 230 .
  • the camera application may support various shooting functions such as photo shooting, video shooting, panorama shooting, and slow motion shooting.
  • applications associated with the camera module 180 may correspond to various types of applications.
  • chat applications web browser applications, e-mail applications, shopping applications, etc. may use the camera module 180 to support video calls, photo/video attachments, streaming services, product images, or product-related VR (virtual reality) shooting functions.
  • VR virtual reality
  • FIG. 3 illustrates a process for correcting image distortion in an electronic device according to an embodiment.
  • An operation subject of the flowchart illustrated in FIG. 3 may be understood as a processor (eg, the processor 220 of FIG. 2 ) or an image signal processor (eg, the image signal processor 130 of FIG. 1 ).
  • the processor 220 may obtain an input image.
  • the input image may be understood as image data or an image frame acquired through the image sensor 120 and input to the processor 220 .
  • the input image may be understood as an image in which distortion occurs in a portion corresponding to the outer edge of the lens when photographing with a wide-angle camera having a wide angle of view.
  • the processor 220 may perform distortion correction on the input image through the following operations.
  • the processor 220 may identify features of each region of the obtained input image, and perform at least one of line correction, face correction, and/or object correction for each region based on the identified features. For example, the processor 220 may perform line correction on a first area and object correction on a second area that is different from the first area.
  • the processor 220 may perform line correction on the obtained input image.
  • the processor 220 may perform correction on a distorted line in the obtained input image. Operation 310 may be described in detail in operations 311 to 319 of FIG. 4 below.
  • the processor 220 may correct a face region of the obtained input image. After detecting a face in the obtained input image, the processor 220 may perform correction on the distorted face. Operation 320 may be described in detail in operations 321 to 325 of FIG. 5 below.
  • the processor 220 may correct the object area of the obtained input image. After detecting an object other than a face in the acquired input image, the processor 220 may perform correction on the distorted object. Operation 330 may be described in detail in operations 331 to 335 of FIG. 5 below.
  • the processor 220 may output, as a resultant image, an image on which at least one of line correction, face area correction, and object area correction has been performed.
  • the processor 220 may output the resulting image through the display 110 as a preview image.
  • the processor 220 may display a preview image of the resulting image on the display 110 through a predetermined image processing process on the resulting image.
  • Operation 301 and operation 303 according to an embodiment correspond to operation 301 and operation 303 of FIG. 3, so descriptions thereof will be omitted.
  • the processor 220 may divide the acquired image into a plurality of grid areas.
  • the processor 220 may divide the acquired image into 12 grid areas of 3 ⁇ 4.
  • the processor 220 may divide the obtained input image based on various grid patterns or the number of grids.
  • the processor 220 may refer to an area formed of four dots in the shape of the grid area.
  • the shape of the grid area may include at least a square, rectangular, trapezoidal, and/or rhombic shape.
  • the processor 220 may detect a line component.
  • the processor 220 may detect line components for each of the plurality of divided grids.
  • the processor 220 may analyze the detected line component.
  • the processor 220 may determine whether there are few line components or whether the line has a certain directivity by detecting line components for each grid area.
  • the processor 220 may determine a candidate region to correct a line.
  • the processor 220 may determine a candidate region for correcting a line based on the detected line component. For example, when distortion occurs in a detected line, the processor 220 may determine a grid area including the line as a candidate area to correct the line.
  • the processor 220 may update a candidate region for line correction. Updating the line correction candidate region may mean adding or excluding the line correction region or changing the intensity of correction among the line correction candidate regions.
  • the processor 220 may update a candidate region for correcting a line based on a distance from the center of an image among a plurality of grid regions, the number of lines included in the grid region, and/or directionality of the lines. .
  • the processor 220 may exclude a lattice region including the line components from the region to be corrected for lines or reduce the intensity of line correction.
  • the processor 220 may not perform the line correction or reduce the strength of the line correction because distortion may further occur when performing the line correction when there are few line components or the directionality of the lines is mixed.
  • the processor 220 may lower the intensity of line correction as the distance from the center of the image decreases. For example, when a face or an object other than a face is detected in an area to be line-corrected, the processor 220 may not perform the line-correction or reduce the strength of the line-correction.
  • the processor 220 may update the candidate region to correct the line based on the face region analysis result of operation 323 of FIG. 5 and the object region analysis result of operation 333 of FIG. 5 . For example, when the weight of the face and/or the object in the grid area where the line component is detected is equal to or greater than the first weight, the processor 220 may not perform line correction or may lower the strength of the correction.
  • the processor 220 may perform line correction.
  • the processor 220 may perform line correction based on calibration data for each region to be line corrected.
  • the calibration data may be data composed of pre-stored tables or data generated in real time based on an image acquired by a camera.
  • the processor 220 may perform line correction based on each weight for each region. For example, the processor 220 may perform line correction on a first grid area based on a first weight and line correction on a second grid area based on a second weight different from the first weight. have.
  • the processor 220 may perform warping.
  • the processor 220 may perform a warping operation on an image on which a stereographic projection has been performed.
  • the processor 220 may perform a warping operation so that a distorted image may be displayed on the display 110 by performing the projection method.
  • the processor 220 may perform image warping by comparing an image on which a projection method has been performed and raw image data obtained through the image sensor 120 .
  • the processor 220 may perform image warping so that the image on which the projection method has been performed corresponds to the position or coordinate information of the original lattice points included in the raw image data.
  • Operation 301 and operation 303 according to an embodiment correspond to operation 301 and operation 303 of FIG. 3, so descriptions thereof will be omitted.
  • the processor 220 may detect a face from an image acquired through the image sensor 120 .
  • the processor 220 may detect at least two or more faces in the image.
  • the processor 220 may detect at least a human face or animal face from the image. It will be clearly understood by those skilled in the art that the face detection may be performed by not only the processor 220, but also the image signal processor 130, other hardware and software modules not shown. Operation 321 may follow or precede operation 311 of FIG. 4 .
  • the processor 220 may analyze the face region.
  • the face area may be understood as an area corresponding to the detected face and/or a grid area including the detected face.
  • the processor 220 may determine whether correction is required by analyzing the facial region.
  • the processor 220 may determine whether to correct based on the detected face information.
  • the processor 220 may determine whether or not to correct based on information about the grid area including the face area.
  • the processor 220 may determine whether correction is necessary based on the location where the face is detected and the size of the face. For example, the processor 220 may determine that correction is necessary when the position of the face is located on the periphery away from the center of the image by a first distance or more and the size of the face is equal to or greater than the first size.
  • the processor 220 may perform distortion correction on the detected face area.
  • the processor 220 may perform correction on an image area corresponding to the detected face.
  • the processor 220 may determine a correction weight based on at least one of the detected face shape, size, and/or face distortion degree.
  • the processor 220 may correct the face region based on the weight.
  • the processor 220 may extract feature points of the detected face and transform coordinates of the feature points.
  • the processor 220 may perform warping after converting the coordinates.
  • the processor 220 may perform a stereographic projection method in correcting the face area.
  • the processor 220 may correct the distorted face area in other ways.
  • the processor 220 may perform correction on the center of the face region with a first intensity, and may perform correction on the periphery of the face region with a second intensity lower than the first intensity.
  • the processor 220 may detect an object from an image acquired through the image sensor 120 .
  • the processor 220 may detect at least two or more objects in the image.
  • the object may mean an object different from the face mentioned in operation 321 above.
  • the objects may mean objects such as a chair, a monitor, a beverage bottle, toilet paper, and a pot. It will be clearly understood by those skilled in the art that the object detection may be performed by not only the processor 220, but also the image signal processor 130, other hardware and software modules not shown. Operation 331 may follow or precede operation 311 of FIG. 4 .
  • the processor 220 may perform object area analysis.
  • the object area may be understood as an area corresponding to the detected object and/or a grid area including the detected object.
  • the processor 220 may determine whether correction is required by analyzing the object area.
  • the processor 220 may determine whether or not to correct based on the detected object information.
  • the processor 220 may determine whether or not to correct based on information about the grid area including the object area.
  • the processor 220 may determine whether the detected object is an object of a predefined class.
  • the processor 220 may set different levels of importance for each class.
  • the processor 220 may determine whether object correction is to be performed and/or the intensity of correction based on the degree of importance. For example, the processor 220 may determine to perform object correction when an object of a predefined class such as a doll, cat, or dog is detected.
  • the processor 220 may determine whether or not to correct the object based on the location where the object is detected and the size of the object. For example, the processor 220 may determine that correction is required when the location of the detected object is located outside the center of the image by a first distance or more and the size of the detected object is greater than or equal to the first size.
  • the processor 220 may determine whether or not to correct the object based on the number of line components detected in the grid area including the object area and/or the directionality of the line components.
  • the processor 220 may perform correction on the detected object.
  • the processor 220 may perform correction on the detected object.
  • the processor 220 may perform correction on an image area corresponding to the detected object.
  • the processor 220 may extract feature points of the detected object and convert coordinates of the feature points.
  • the processor 220 may perform warping after converting the coordinates.
  • the processor 220 may perform a stereographic projection method in correcting the object area.
  • the processor 220 may correct the distorted object area in other ways.
  • the processor 220 may perform correction on the center of the object area with a first intensity, and may perform correction on a peripheral portion of the object area with a second intensity lower than the first intensity.
  • FIG. 6 is a flowchart illustrating a process for correcting a distorted image in an electronic device according to an embodiment.
  • the processor 220 may acquire an image frame through the image sensor 120 .
  • the processor 220 may divide the acquired image frame into a plurality of grid areas.
  • the processor 220 may detect at least one element among at least one object or line component in the obtained image frame.
  • the at least one object may be an object such as a face or an object.
  • the processor 220 may determine an area to perform line distortion correction by analyzing a grid area including at least one detected element.
  • the processor 220 may determine a candidate region to perform line distortion correction.
  • the processor 220 may update a candidate region based on information on the determined candidate region. Since this is explained through FIGS. 3 to 5, it will be briefly described here.
  • the processor 220 performs line distortion correction on the first grid area based on the first weight, and performs line distortion correction on the second grid area based on the second weight.
  • the processor 220 may perform line distortion correction on the first grid region based on the first weight. have.
  • the processor 220 corrects line distortion based on a second weight lower than the first weight for the second grid region. can be performed.
  • the processor 220 may display an image frame on which distortion correction is performed on a display.
  • the processor 220 may output, as a preview image, an image frame on which at least one of line correction, face area correction, and object area correction has been performed through the display 110 .
  • FIG. 7 is a diagram illustrating that an electronic device divides and analyzes an input image into grid areas according to an exemplary embodiment.
  • the first image 700 may be an image acquired through the camera module 180 .
  • the first image 700 may be an image captured by a wide-angle camera and/or an ultra-wide-angle camera.
  • the first image 700 may be an image in which distortion occurs in a portion corresponding to the outer edge of the lens when light is incident through the wide-angle lens and/or the ultra-wide-angle lens. For example, distortion may occur in a mountain ridge 711, a cloud 721, a human face 731, and a tree 741 included in a grid area outside the first image 700.
  • the processor 220 may detect line components in at least one grid area.
  • the processor 220 may perform line correction on the distorted line component.
  • the processor 220 may detect a mountain ridge 711 as a line component in the first grid area 710 .
  • the processor 220 may perform correction by determining strength of line correction based on the directionality and number of detected lines. For example, when the number of detected line components is small and the directionality is not regular, the processor 220 may perform correction by lowering the intensity of line correction.
  • the processor 220 may determine whether or not to correct based on information about the grid area in which the line component is detected. For example, the processor 220 may perform line correction on the distorted mountain ridge 711 when the specific gravity of the object detected in the first grid area 710 is less than or equal to a certain level.
  • the processor 220 may detect line components and objects in at least one grid area.
  • the processor 220 may detect a mountain ridge 711, which is a line component, and an object (eg, a cloud 722) in the second grid area 720.
  • the processor 220 may perform image correction in consideration of the line component detected in the second grid area 720 and the specific gravity of the object. For example, the processor 220 may perform both line correction and object correction on the second grid area 720 .
  • the processor 220 may perform line correction on the second grid area 720 without object correction.
  • the processor 220 may perform object correction without line correction on the second grid area 720 .
  • the processor 220 may detect a face in at least one grid area.
  • the processor 220 may perform face correction on the distorted face.
  • the processor 220 may detect the face 731 in the third grid area 730 .
  • the processor 220 may perform face correction based on the weight of line components included in the third grid area 730 and/or the weight of the distorted face.
  • the processor 220 may detect an object included in at least one grid area.
  • the processor 220 may perform object correction on the distorted object. For example, when the processor 220 detects an object (eg, a tree 741) without detecting a line component in the fourth grid area 740, it may perform object correction on the distorted object. .
  • FIG. 8 illustrates a first image 700 acquired by an electronic device and a region obtained by cropping a part of the first image 700 according to an exemplary embodiment.
  • FIG. 8 is described based on the face 811, it is obvious to those skilled in the art that it can be applied to objects other than the face.
  • the processor 220 may detect the face 811 included in the first image 700 .
  • the processor 220 may set a face area 810 including the detected face 811 .
  • the processor 220 may extract feature points from the face area 810 and transform coordinates of the feature points.
  • the processor 220 may perform warping after converting the coordinates.
  • FIG. 9 illustrates matching of mismatched cell points generated in a process of performing warping in an electronic device according to an embodiment.
  • the cell points do not match during the process of warping by the processor 220 .
  • the first point 901 and the second point 902 may not match.
  • the processor 220 may match inconsistent cell points in a warping process.
  • the processor 220 may adjust movement values of cell points to gradually change. However, since moving the first point 901 to match the second point 902 or moving the second point 902 to match the first point 901 does not naturally perform distortion correction, The point 901 and the second point 902 may be moved. In other words, the processor 220 may match the first point 901 and the second point 902 at an intermediate value 903 of the first point 901 and the second point 902 .
  • FIG. 10 is a block diagram of an electronic device 1001 within a network environment 1000 according to various embodiments.
  • an electronic device 1001 communicates with an electronic device 1002 through a first network 1098 (eg, a short-distance wireless communication network) or through a second network 1099. It is possible to communicate with the electronic device 1004 or the server 1008 through (eg, a long-distance wireless communication network). According to an embodiment, the electronic device 1001 may communicate with the electronic device 1004 through the server 1008.
  • a first network 1098 eg, a short-distance wireless communication network
  • the server 1008 eg, a long-distance wireless communication network
  • the electronic device 1001 may communicate with the electronic device 1004 through the server 1008.
  • the electronic device 1001 includes a processor 1020, a memory 1030, an input module 1050, an audio output module 1055, a display module 1060, an audio module 1070, a sensor module ( 1076), interface 1077, connection terminal 1078, haptic module 1079, camera module 1080, power management module 1088, battery 1089, communication module 1090, subscriber identification module 1096 , or an antenna module 1097.
  • a processor 1020 e.g, a memory 1030, an input module 1050, an audio output module 1055, a display module 1060, an audio module 1070, a sensor module ( 1076), interface 1077, connection terminal 1078, haptic module 1079, camera module 1080, power management module 1088, battery 1089, communication module 1090, subscriber identification module 1096 , or an antenna module 1097.
  • at least one of these components eg, the connection terminal 1078
  • some of these components eg, sensor module 1076,
  • the processor 1020 for example, executes software (eg, the program 1040) to cause at least one other component (eg, hardware or software component) of the electronic device 1001 connected to the processor 1020. It can control and perform various data processing or calculations. According to one embodiment, as at least part of data processing or operation, processor 1020 transfers commands or data received from other components (eg, sensor module 1076 or communication module 1090) to volatile memory 1032. , process commands or data stored in the volatile memory 1032 , and store resultant data in the non-volatile memory 1034 .
  • software eg, the program 1040
  • processor 1020 transfers commands or data received from other components (eg, sensor module 1076 or communication module 1090) to volatile memory 1032. , process commands or data stored in the volatile memory 1032 , and store resultant data in the non-volatile memory 1034 .
  • the processor 1020 may include a main processor 1021 (eg, a central processing unit or an application processor) or a secondary processor 1023 (eg, a graphic processing unit, a neural network processing unit ( NPU: neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor).
  • a main processor 1021 eg, a central processing unit or an application processor
  • a secondary processor 1023 eg, a graphic processing unit, a neural network processing unit ( NPU: neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor.
  • NPU neural network processing unit
  • NPU neural processing unit
  • image signal processor sensor hub processor
  • communication processor e.g., a communication processor.
  • the auxiliary processor 1023 may use less power than the main processor 1021 or be set to be specialized for a designated function.
  • the auxiliary processor 1023 may be implemented separately from or as part of the main processor 1021 .
  • the secondary processor 1023 may, for example, take the place of the main processor 1021 while the main processor 1021 is inactive (eg sleep), or the main processor 1021 is active (eg application execution). ) state, together with the main processor 1021, at least one of the components of the electronic device 1001 (eg, the display module 1060, the sensor module 1076, or the communication module 1090) It is possible to control at least some of the related functions or states.
  • the auxiliary processor 1023 eg, image signal processor or communication processor
  • may be implemented as part of other functionally related components eg, camera module 1080 or communication module 1090). have.
  • the auxiliary processor 1023 may include a hardware structure specialized for processing an artificial intelligence model.
  • AI models can be created through machine learning. Such learning may be performed, for example, in the electronic device 1001 itself where artificial intelligence is performed, or may be performed through a separate server (eg, the server 1008).
  • the learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, but in the above example Not limited.
  • the artificial intelligence model may include a plurality of artificial neural network layers.
  • Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the foregoing, but is not limited to the foregoing examples.
  • the artificial intelligence model may include, in addition or alternatively, software structures in addition to hardware structures.
  • the memory 1030 may store various data used by at least one component (eg, the processor 1020 or the sensor module 1076) of the electronic device 1001 .
  • the data may include, for example, input data or output data for software (eg, the program 1040) and commands related thereto.
  • the memory 1030 may include a volatile memory 1032 or a non-volatile memory 1034 .
  • the program 1040 may be stored as software in the memory 1030 and may include, for example, an operating system 1042 , middleware 1044 , or an application 1046 .
  • the input module 1050 may receive a command or data to be used for a component (eg, the processor 1020) of the electronic device 1001 from an outside of the electronic device 1001 (eg, a user).
  • the input module 1050 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).
  • the sound output module 1055 may output sound signals to the outside of the electronic device 1001 .
  • the sound output module 1055 may include, for example, a speaker or receiver.
  • the speaker can be used for general purposes such as multimedia playback or recording playback.
  • a receiver may be used to receive an incoming call. According to one embodiment, the receiver may be implemented separately from the speaker or as part of it.
  • the display module 1060 may visually provide information to the outside of the electronic device 1001 (eg, a user).
  • the display module 1060 may include, for example, a display, a hologram device, or a projector and a control circuit for controlling the device.
  • the display module 1060 may include a touch sensor configured to detect a touch or a pressure sensor configured to measure the intensity of force generated by the touch.
  • the audio module 1070 may convert sound into an electrical signal or vice versa. According to an embodiment, the audio module 1070 acquires sound through the input module 1050, the sound output module 1055, or an external electronic device connected directly or wirelessly to the electronic device 1001 (eg: Sound may be output through the electronic device 1002 (eg, a speaker or a headphone).
  • the audio module 1070 acquires sound through the input module 1050, the sound output module 1055, or an external electronic device connected directly or wirelessly to the electronic device 1001 (eg: Sound may be output through the electronic device 1002 (eg, a speaker or a headphone).
  • the sensor module 1076 detects an operating state (eg, power or temperature) of the electronic device 1001 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the detected state. can do.
  • the sensor module 1076 may include, for example, a gesture sensor, a gyro sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a bio sensor, It may include a temperature sensor, humidity sensor, or light sensor.
  • the interface 1077 may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device 1001 to an external electronic device (eg, the electronic device 1002).
  • the interface 1077 may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.
  • HDMI high definition multimedia interface
  • USB universal serial bus
  • SD card interface Secure Digital Card
  • connection terminal 1078 may include a connector through which the electronic device 1001 may be physically connected to an external electronic device (eg, the electronic device 1002).
  • the connection terminal 1078 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).
  • the haptic module 1079 may convert electrical signals into mechanical stimuli (eg, vibration or motion) or electrical stimuli that a user can perceive through tactile or kinesthetic senses.
  • the haptic module 1079 may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.
  • the camera module 1080 may capture still images and moving images. According to one embodiment, the camera module 1080 may include one or more lenses, image sensors, image signal processors, or flashes.
  • the power management module 1088 may manage power supplied to the electronic device 1001 .
  • the power management module 1088 may be implemented as at least part of a power management integrated circuit (PMIC), for example.
  • PMIC power management integrated circuit
  • the battery 1089 may supply power to at least one component of the electronic device 1001 .
  • the battery 1089 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.
  • the communication module 1090 is a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 1001 and an external electronic device (eg, the electronic device 1002, the electronic device 1004, or the server 1008). Establishment and communication through the established communication channel may be supported.
  • the communication module 1090 may include one or more communication processors that operate independently of the processor 1020 (eg, an application processor) and support direct (eg, wired) communication or wireless communication.
  • the communication module 1090 is a wireless communication module 1092 (eg, a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 1094 (eg, : a local area network (LAN) communication module or a power line communication module).
  • the corresponding communication module is a first network 1098 (eg, a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network 1099 (eg, a legacy communication module).
  • the wireless communication module 1092 uses subscriber information (eg, International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 1096 within a communication network such as the first network 1098 or the second network 1099.
  • IMSI International Mobile Subscriber Identifier
  • the wireless communication module 1092 may support a 5G network after a 4G network and a next-generation communication technology, for example, NR access technology (new radio access technology).
  • NR access technologies include high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and access of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low latency (URLLC)). -latency communications)) can be supported.
  • the wireless communication module 1092 may support a high frequency band (eg, mmWave band) to achieve a high data rate, for example.
  • a high frequency band eg, mmWave band
  • the wireless communication module 1092 uses various technologies for securing performance in a high frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), and full-dimensional multiplexing. Technologies such as input/output (FD-MIMO: full dimensional MIMO), array antenna, analog beam-forming, or large scale antenna may be supported.
  • the wireless communication module 1092 may support various requirements defined for the electronic device 1001, an external electronic device (eg, the electronic device 1004), or a network system (eg, the second network 1099).
  • the wireless communication module 1092 may be used to realize peak data rate (eg, 20 Gbps or more) for realizing eMBB, loss coverage (eg, 164 dB or less) for realizing mMTC, or U-plane latency (for realizing URLLC).
  • peak data rate eg, 20 Gbps or more
  • loss coverage eg, 164 dB or less
  • U-plane latency for realizing URLLC.
  • DL downlink
  • UL uplink each of 0.5 ms or less, or round trip 1 ms or less
  • the antenna module 1097 may transmit or receive signals or power to the outside (eg, an external electronic device).
  • the antenna module 1097 may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (eg, PCB).
  • the antenna module 1097 may include a plurality of antennas (eg, an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 1098 or the second network 1099 is selected from the plurality of antennas by, for example, the communication module 1090. can be chosen A signal or power may be transmitted or received between the communication module 1090 and an external electronic device through the selected at least one antenna.
  • other components eg, a radio frequency integrated circuit (RFIC) may be additionally formed as a part of the antenna module 1097 in addition to the radiator.
  • RFIC radio frequency integrated circuit
  • the antenna module 1097 may form a mmWave antenna module.
  • the mmWave antenna module includes a printed circuit board, an RFIC disposed on or adjacent to a first surface (eg, a lower surface) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, array antennas) disposed on or adjacent to a second surface (eg, a top surface or a side surface) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.
  • peripheral devices eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)
  • signal e.g. commands or data
  • commands or data may be transmitted or received between the electronic device 1001 and the external electronic device 1004 through the server 1008 connected to the second network 1099 .
  • Each of the external electronic devices 1002 or 1004 may be the same as or different from the electronic device 1001 .
  • all or part of operations executed in the electronic device 1001 may be executed in one or more external electronic devices among the external electronic devices 1002 , 1004 , or 1008 .
  • the electronic device 1001 when the electronic device 1001 needs to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device 1001 instead of executing the function or service by itself.
  • one or more external electronic devices may be requested to perform the function or at least part of the service.
  • One or more external electronic devices receiving the request may execute at least a part of the requested function or service or an additional function or service related to the request, and deliver the execution result to the electronic device 1001 .
  • the electronic device 1001 may provide the result as at least part of a response to the request as it is or after additional processing.
  • cloud computing distributed computing, mobile edge computing (MEC), or client-server computing technology may be used.
  • the electronic device 1001 may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing.
  • the external electronic device 1004 may include an internet of things (IoT) device.
  • Server 1008 may be an intelligent server using machine learning and/or neural networks.
  • the external electronic device 1004 or server 1008 may be included in the second network 1099.
  • the electronic device 1001 may be applied to intelligent services (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.
  • a camera module 1080 includes a lens assembly 1110, a flash 1120, an image sensor 1130, an image stabilizer 1140, a memory 1150 (eg, a buffer memory), or an image signal processor. (1160).
  • the lens assembly 1110 may collect light emitted from a subject that is an image capture target.
  • the lens assembly 1110 may include one or more lenses.
  • the camera module 1080 may include a plurality of lens assemblies 1110. In this case, the camera module 1080 may form, for example, a dual camera, a 360-degree camera, or a spherical camera.
  • Some of the plurality of lens assemblies 1110 may have the same lens properties (eg, angle of view, focal length, auto focus, f number, or optical zoom), or at least one lens assembly may have the same lens properties as another lens assembly. may have one or more lens properties different from the lens properties of .
  • the lens assembly 1110 may include, for example, a wide-angle lens or a telephoto lens.
  • the flash 1120 may emit light used to enhance light emitted or reflected from a subject.
  • the flash 1120 may include one or more light emitting diodes (eg, a red-green-blue (RGB) LED, a white LED, an infrared LED, or an ultraviolet LED), or a xenon lamp.
  • the image sensor 1130 may acquire an image corresponding to the subject by converting light emitted or reflected from the subject and transmitted through the lens assembly 1110 into an electrical signal.
  • the image sensor 1130 may be, for example, one image sensor selected from among image sensors having different properties, such as an RGB sensor, a black and white (BW) sensor, an IR sensor, or a UV sensor, It may include a plurality of image sensors having a property, or a plurality of image sensors having other properties.
  • Each image sensor included in the image sensor 1130 may be implemented using, for example, a charged coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor.
  • CCD charged coupled device
  • CMOS complementary metal oxide semiconductor
  • the image stabilizer 1140 moves at least one lens or image sensor 1130 included in the lens assembly 1110 in a specific direction in response to movement of the camera module 1080 or the electronic device 1001 including the same. Operation characteristics of the image sensor 1130 may be controlled (eg, read-out timing is adjusted, etc.). This makes it possible to compensate at least part of the negative effect of the movement on the image being taken.
  • the image stabilizer 1140 may include a gyro sensor (not shown) or an acceleration sensor (not shown) disposed inside or outside the camera module 1080. Such a movement of the camera module 1080 or the electronic device 1001 can be detected using .
  • the image stabilizer 1140 may be implemented as, for example, an optical image stabilizer.
  • the memory 1150 may at least temporarily store at least a portion of an image acquired through the image sensor 1130 for a next image processing task. For example, when image acquisition is delayed according to the shutter, or when a plurality of images are acquired at high speed, the acquired original image (eg, a Bayer-patterned image or a high-resolution image) is stored in the memory 1150 and , a copy image (eg, a low resolution image) corresponding thereto may be previewed through the display device 1060 . Thereafter, when a specified condition is satisfied (eg, a user input or a system command), at least a part of the original image stored in the memory 1150 may be acquired and processed by, for example, the image signal processor 1160 . According to an embodiment, the memory 1150 may be configured as at least a part of the memory 1030 or as a separate memory operated independently of the memory 1030 .
  • a specified condition eg, a user input or a system command
  • the image signal processor 1160 may perform one or more image processes on an image acquired through the image sensor 1130 or an image stored in the memory 1150 .
  • the one or more image processes for example, depth map generation, 3D modeling, panorama generation, feature point extraction, image synthesis, or image compensation (eg, noise reduction, resolution adjustment, brightness adjustment, blurring ( blurring, sharpening, or softening.
  • the image signal processor 1160 may include at least one of the components included in the camera module 1080 (eg, an image sensor). 1130) may be controlled (eg, exposure time control, read-out timing control, etc.)
  • the image processed by the image signal processor 1160 is stored again in the memory 1150 for further processing.
  • the image signal processor 1160 may be configured as at least a part of the processor 1020 or may be configured as a separate processor that operates independently of the processor 1020.
  • the image signal processor 1160 may be configured as a processor 1020 When configured as a separate processor, at least one image processed by the image signal processor 1160 may be displayed through the display device 1060 as it is by the processor 1020 or after additional image processing.
  • the electronic device 1001 may include a plurality of camera modules 1080 each having different properties or functions.
  • at least one of the plurality of camera modules 1080 may be a wide-angle camera and at least the other may be a telephoto camera.
  • at least one of the plurality of camera modules 1080 may be a front camera and at least the other may be a rear camera.
  • an electronic device eg, the electronic device 100 of FIG. 2
  • an image sensor eg, the image sensor 120 of FIG. 2
  • a display eg, the display 110 of FIG. 2
  • at least one processor eg, the processor 220 of FIG. 2 operatively connected to the image sensor and the display, wherein the at least one processor obtains an image frame through the image sensor.
  • a second grid area among the plurality of grid areas may perform line distortion correction based on the second weight, and display the image frame on which the distortion correction is performed on the display.
  • the at least one processor may determine an area in which the line distortion correction is to be performed based on the number of line components and directions of the line components.
  • the first lattice region may be a region in which the specific gravity of the line elements is greater than or equal to the first specific gravity
  • the second lattice region may be an region in which the specific gravity of the line elements is less than the first specific gravity
  • the at least one processor performs a stereographic projection on the at least one detected object, and image warping based on a grid node whose location is changed by the stereographic projection. (warping) can be performed.
  • the at least one processor may match a first lattice point and a second lattice point adjacent to the first lattice point.
  • the at least one processor is configured to match the first lattice point and the second lattice point with an intermediate value of a coordinate value for the first lattice point and a coordinate value for the second lattice point.
  • the one or more processors may control the intensity of correction for the line distortion based on the size and position of at least one detected object among the one or more detected elements.
  • the at least one processor may determine whether the at least one object is included in a predefined class.
  • the at least one object may include a human face or an object.
  • the at least one processor performs object correction on the detected at least one object, and the image frame on which the line distortion correction and the object correction have been performed is stored in the image frame. can be displayed on the display.
  • the operating method of the electronic device includes obtaining an image frame through an image sensor and dividing the image frame into a plurality of grid areas, the acquired image frame Detecting at least one element among at least one object or line component, analyzing a lattice area including the detected at least one element, and determining an area to perform line distortion correction among the plurality of lattice areas.
  • a first lattice area among the plurality of lattice areas performs line distortion correction based on a first weight
  • a second lattice area among the plurality of lattice areas performs line distortion correction based on a second weight It may include an operation of performing line distortion correction and an operation of displaying the image frame on which the distortion correction is performed on a display.
  • an operation of determining an area in which the line distortion correction is to be performed based on the number of line components and the direction of the line components may be included.
  • the first lattice region may be a region in which the specific gravity of the line elements is greater than or equal to the first specific gravity
  • the second lattice region may be an region in which the specific gravity of the line elements is less than the first specific gravity
  • a stereographic projection is performed on the at least one detected object, and image warping is performed based on a grid node whose position is changed by the stereographic projection. action may be included.
  • performing warping on the lattice points may include matching a first lattice point and a second lattice point adjacent to the first lattice point.
  • an operation of matching the first lattice point and the second lattice point with an intermediate value of a coordinate value for the first lattice point and a coordinate value for the second lattice point may be included.
  • an operation of controlling the strength of correction for the line distortion based on the size and position of at least one detected object among the at least one detected element may be included.
  • an operation of determining whether the at least one object is included in a pre-specified class may be included.
  • the at least one object may include a human face or an object.
  • an operation of performing object correction on the at least one detected object and an operation of displaying the image frame on which the line distortion correction and the object correction have been performed on the display can include
  • Electronic devices may be devices of various types.
  • the electronic device may include, for example, a portable communication device (eg, a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a home appliance.
  • a portable communication device eg, a smart phone
  • a computer device e.g., a smart phone
  • a portable multimedia device e.g., a portable medical device
  • a camera e.g., a portable medical device
  • a camera e.g., a portable medical device
  • a camera e.g., a camera
  • a wearable device e.g., a smart bracelet
  • first, second, or first or secondary may simply be used to distinguish that component from other corresponding components, and may refer to that component in other respects (eg, importance or order) is not limited.
  • a (eg, first) component is said to be “coupled” or “connected” to another (eg, second) component, with or without the terms “functionally” or “communicatively.”
  • the certain component may be connected to the other component directly (eg by wire), wirelessly, or through a third component.
  • module used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and is interchangeably interchangeable with terms such as, for example, logic, logic blocks, components, or circuits.
  • a module may be an integrally constructed component or a minimal unit of components or a portion thereof that performs one or more functions.
  • the module may be implemented in the form of an application-specific integrated circuit (ASIC).
  • ASIC application-specific integrated circuit
  • a storage medium eg, internal memory 1036 or external memory 1038
  • a machine eg, electronic device 1001
  • a processor eg, the processor 1020
  • a device eg, the electronic device 1001
  • the one or more instructions may include code generated by a compiler or code executable by an interpreter.
  • the device-readable storage medium may be provided in the form of a non-transitory storage medium.
  • the storage medium is a tangible device and does not contain a signal (e.g. electromagnetic wave), and this term refers to the case where data is stored semi-permanently in the storage medium. It does not discriminate when it is temporarily stored.
  • a signal e.g. electromagnetic wave
  • the method according to various embodiments disclosed in this document may be included and provided in a computer program product.
  • Computer program products may be traded between sellers and buyers as commodities.
  • a computer program product is distributed in the form of a device-readable storage medium (e.g. compact disc read only memory (CD-ROM)), or through an application store (e.g. Play Store TM ) or on two user devices (e.g. It can be distributed (eg downloaded or uploaded) online, directly between smart phones.
  • a device e.g. compact disc read only memory (CD-ROM)
  • an application store e.g. Play Store TM
  • It can be distributed (eg downloaded or uploaded) online, directly between smart phones.
  • at least part of the computer program product may be temporarily stored or temporarily created in a storage medium readable by a device such as a manufacturer's server, an application store server, or a relay server's memory.
  • each component (eg, module or program) of the components described above may include a single object or a plurality of objects, and some of the multiple objects may be separately disposed in other components.
  • one or more components or operations among the aforementioned components may be omitted, or one or more other components or operations may be added.
  • a plurality of components eg modules or programs
  • the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by a corresponding component of the plurality of components prior to the integration. .
  • operations performed by modules, programs, or other components are executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations are executed in a different order, omitted, or , or one or more other operations may be added.

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  • Engineering & Computer Science (AREA)
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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
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Abstract

Un dispositif électronique, selon un mode de réalisation, comprend : un capteur d'image ; un écran ; et au moins un processeur connecté fonctionnellement au capteur d'image et à l'écran. Ledit processeur : acquiert une trame d'image par l'intermédiaire du capteur d'image et segmente la trame d'image en une pluralité de régions de réseau ; détecte, dans la trame d'image acquise, au moins un élément parmi au moins un objet ou un composant de ligne ; en analysant une région de réseau comprenant ledit élément détecté, détermine des régions, parmi la pluralité de régions de réseau, où une correction de distorsion de ligne doit être effectuée ; sur la base des régions déterminées, réalise une correction de distorsion de ligne sur une première région de réseau, parmi la pluralité de régions de réseau, sur la base d'une première valeur pondérée, et effectue une correction de distorsion de ligne sur une seconde région de réseau, parmi la pluralité de régions de réseau, sur la base d'une seconde valeur pondérée ; et peut afficher la trame d'image à distorsion corrigée sur l'écran. Divers autres modes de réalisation sont possibles, tels qu'identifiés dans la spécification.
PCT/KR2022/006737 2021-05-11 2022-05-11 Procédé de correction de distorsion d'image et dispositif électronique associé WO2022240186A1 (fr)

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KR1020210060863A KR20220153366A (ko) 2021-05-11 2021-05-11 이미지 왜곡을 보정하는 방법 및 그 전자 장치

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KR101679290B1 (ko) * 2009-11-17 2016-11-24 삼성전자 주식회사 영상 처리 방법 및 장치
KR101904480B1 (ko) * 2014-12-26 2018-10-04 재단법인 다차원 스마트 아이티 융합시스템 연구단 카메라의 왜곡을 고려한 물체 인식 시스템 및 방법
KR102028469B1 (ko) * 2018-01-15 2019-10-04 주식회사 스트리스 어안 렌즈 및 전방위 영상의 왜곡 제거를 위한 장치 및 방법
US20190355090A1 (en) * 2017-01-19 2019-11-21 Sony Interactive Entertainment Inc. Image generation apparatus and image display control apparatus
KR20200045682A (ko) * 2018-10-23 2020-05-06 한국전자통신연구원 Hlbp 디스크립터 정보를 이용한 시차 최소화 스티칭 장치 및 방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101679290B1 (ko) * 2009-11-17 2016-11-24 삼성전자 주식회사 영상 처리 방법 및 장치
KR101904480B1 (ko) * 2014-12-26 2018-10-04 재단법인 다차원 스마트 아이티 융합시스템 연구단 카메라의 왜곡을 고려한 물체 인식 시스템 및 방법
US20190355090A1 (en) * 2017-01-19 2019-11-21 Sony Interactive Entertainment Inc. Image generation apparatus and image display control apparatus
KR102028469B1 (ko) * 2018-01-15 2019-10-04 주식회사 스트리스 어안 렌즈 및 전방위 영상의 왜곡 제거를 위한 장치 및 방법
KR20200045682A (ko) * 2018-10-23 2020-05-06 한국전자통신연구원 Hlbp 디스크립터 정보를 이용한 시차 최소화 스티칭 장치 및 방법

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