WO2018014828A1 - 识别二维码位置的方法及其*** - Google Patents
识别二维码位置的方法及其*** Download PDFInfo
- Publication number
- WO2018014828A1 WO2018014828A1 PCT/CN2017/093370 CN2017093370W WO2018014828A1 WO 2018014828 A1 WO2018014828 A1 WO 2018014828A1 CN 2017093370 W CN2017093370 W CN 2017093370W WO 2018014828 A1 WO2018014828 A1 WO 2018014828A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- dimensional code
- position information
- positioning block
- location information
- point position
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
- G06K7/1452—Methods for optical code recognition including a method step for retrieval of the optical code detecting bar code edges
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1408—Methods for optical code recognition the method being specifically adapted for the type of code
- G06K7/1417—2D bar codes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/14—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
- G06K7/1404—Methods for optical code recognition
- G06K7/1439—Methods for optical code recognition including a method step for retrieval of the optical code
- G06K7/1443—Methods for optical code recognition including a method step for retrieval of the optical code locating of the code in an image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/20—Scenes; Scene-specific elements in augmented reality scenes
Definitions
- the present application relates to the field of computer technology, and in particular, to a method for identifying a location of a two-dimensional code and a system thereof.
- Augmented Reality is a new technology that integrates real world information and virtual world information "seamlessly". It is an entity information that is difficult to experience in a certain time and space of the real world. Visual information, sound, taste, touch, etc., through computer technology, simulation and then superimposed into the real world is perceived by human senses, thus achieving a sensory experience beyond reality.
- the augmented reality technology using the two-dimensional code as a marker (Marker) in the prior art mainly has the following two implementation schemes:
- the scheme uses the two-dimensional code contour as the feature point set, and the system presets a two-dimensional code contour feature point set, and then applies preset feature point sets to other captured two-dimensional codes to match.
- the main disadvantage of this scheme is that since the pattern of the two-dimensional code is different due to different code values, including the pattern size and the density of black and white blocks, the contour of the two-dimensional code does not have stable features, resulting in no tracking accuracy. Stable (highly accurate with contours and low accuracy with large contours).
- the scheme first decodes the two-dimensional code to obtain a code value string, and then regenerates a standard two-dimensional code picture identical to the captured two-dimensional code, and then performs feature point extraction on the newly generated two-dimensional code picture, and the obtained feature is obtained.
- the point set is used as a system preset feature point set.
- the main disadvantage of this scheme is that for any new QR code, the system needs to repeat the above steps to generate a new set of preset feature points, which is time consuming and slows down the processing speed of the entire system.
- the main purpose of the present application is to provide a method for identifying a position of a two-dimensional code and a system thereof, which solves the problem of slow recognition speed and low tracking accuracy of the prior art Augmented reality scheme using a two-dimensional code as a marker.
- a method for identifying a position of a two-dimensional code includes: acquiring a two-dimensional code in an image; performing feature detection according to a primary positioning block of the two-dimensional code, and identifying the second Position information in the dimension code; determining spatial position information of the two-dimensional code in the image according to position information in the two-dimensional code.
- the method further comprises: tracking location information in the two-dimensional code.
- the step of performing feature detection according to the primary positioning block of the two-dimensional code includes: determining one or more primary positioning blocks of the two-dimensional code; respectively acquiring a central point position information of each primary positioning block And a plurality of corner point position information; the center point position information and the corner point position information of the obtained main positioning block are used as feature point sets to perform feature detection.
- the step of performing feature detection according to the primary positioning block of the two-dimensional code includes: determining one or more primary positioning blocks of the two-dimensional code; respectively acquiring a central point position information of each primary positioning block And a plurality of black and white pixel boundary edge center point position information; the center point position information of the obtained main positioning block and the black and white pixel boundary edge center point position information are used as feature point sets to perform feature detection.
- the step of determining the spatial location information of the two-dimensional code in the image according to the location information in the two-dimensional code includes: acquiring preset standard location information; and using the standard location information and the location The position information in the two-dimensional code is matched to obtain the spatial position information.
- the two-dimensional code is a fast response QR two-dimensional code.
- the method further includes: acquiring virtual application data corresponding to the two-dimensional code; and determining a spatial location of the virtual application data according to the spatial location information.
- a system for identifying a location of a two-dimensional code including: an acquisition module, configured to acquire a two-dimensional code in an image; and an identification module, configured to perform a feature according to the primary positioning block of the two-dimensional code Detecting, identifying location information in the two-dimensional code; a spatial location determining module, configured to determine spatial location information of the two-dimensional code in the image according to location information in the two-dimensional code.
- the system further includes: a tracking module, configured to track location information in the two-dimensional code.
- the identification module includes: a first determining module, configured to determine one or more primary positioning blocks of the two-dimensional code; and a first acquiring module, configured to separately acquire a central location point information of each primary positioning block And a plurality of corner point position information; the first detecting module is configured to use the center point position information and the corner point position information of the acquired main positioning block as a feature point set to perform feature detection.
- the first obtaining module acquires 12, 8 or 4 corner point position information of each main positioning block.
- the identification module includes: a second determining module, configured to determine one or more primary positioning blocks of the two-dimensional code; and a second acquiring module, configured to acquire a central point location information of each primary positioning block And a plurality of black and white pixel boundary edge center point position information; the second detecting module is configured to perform feature detection on the acquired center point position information of the main positioning block and the black and white pixel boundary edge center point position information as a feature point set.
- the second obtaining module acquires 12, 8 or 4 black and white pixel boundary edge center point position information of each main positioning block.
- the space location determining module is configured to: acquire preset standard location information, and match the standard location information with location information in the two-dimensional code to obtain the spatial location information.
- the two-dimensional code is a fast response QR two-dimensional code.
- the system further includes: a virtual application data acquiring module, configured to acquire virtual application data corresponding to the two-dimensional code; and a location updating module, configured to update a spatial location of the virtual application data according to the spatial location information .
- the present application recognizes the position of the two-dimensional code by using the two-dimensional code as the Marker and performing feature detection on the preset position of the main positioning block of the two-dimensional code.
- the feature point set of the extracted two-dimensional code has a fixed relative position, is unique, is not easy to be confused, and has a good tracking effect.
- FIG. 1 is a flow chart of a method of identifying a location of a two-dimensional code in accordance with one embodiment of the present application
- FIGS. 2A and 2B are diagrams showing the composition of a main positioning block of a QR code according to an embodiment of the present application
- 3A and 3B are schematic diagrams of feature point extraction according to an embodiment of the present application.
- FIG. 4 is a schematic diagram of feature point extraction according to another embodiment of the present application.
- FIG. 5 is a flowchart of a method of identifying a location of a two-dimensional code according to another embodiment of the present application.
- FIG. 6 is a structural block diagram of a system for identifying a location of a two-dimensional code according to an embodiment of the present application
- FIG. 7A and 7B are structural block diagrams of an identification module according to an embodiment of the present application.
- FIG. 8 is a structural block diagram of a system for recognizing a position of a two-dimensional code for augmented reality technology according to another embodiment of the present application.
- FIG. 1 is a flowchart of a method for identifying a location of a two-dimensional code according to an embodiment of the present application. As shown in FIG. 1, the method includes:
- Step S102 acquiring a two-dimensional code in the image.
- the real scene image containing the two-dimensional code is acquired by the camera device of the terminal device, and the terminal device may be a smart phone, a tablet computer, a digital camera or the like. Then, preprocessing the input two-dimensional code image, specifically comprising: gray-converting the image to obtain gray The degree image is subjected to binarization processing on the grayscale image.
- the two-dimensional code may be a QR code.
- Step S104 Perform feature detection according to the primary positioning block of the two-dimensional code, and identify location information in the two-dimensional code.
- the position information in the two-dimensional code includes position information such as a center point position of the main positioning block of the two-dimensional code, a corner point position, and a black-and-white pixel boundary edge center point position.
- the position information of the two-dimensional code on the plane can be determined by the position information described above, that is, the spatial position information such as the direction, the rotation angle, and the inclination angle of the two-dimensional code is determined.
- FIG. 2A is a structural diagram of a main positioning block of a QR code.
- the positioning of the QR code includes two types: a main positioning block and an auxiliary positioning block, wherein the main positioning block includes an upper left corner 201, an upper right corner 202, and a lower left corner 203.
- a large back-shaped area, and the auxiliary positioning block is a small black border box in the middle.
- the main positioning block is characterized in that the length ratio of the line segments composed of black and white pixels is 1:1:3:1:1, and the feature extraction and positioning of the code can be performed on the two-dimensional code. Since the main positioning block is common to all the two-dimensional codes, and the shape and position of the pattern are fixed, it can be used as a universal identifier of the two-dimensional code pattern, that is, the main positioning block can be used as a common feature point set of the two-dimensional code pattern.
- the feature extraction process of the primary positioning block is described in detail below.
- a center point and a corner point of the main positioning block may be employed as a feature point set.
- the corner point is a point at a right angle in the main positioning block, and the corner point is also a point where the pixel in the image changes sharply.
- the center point 301 Taking the main positioning block center point 301 as a starting point and detecting the corner points around it, it can be seen that there is a first group of 4 corner points (311, 312, 313 and 314) closest to the center point 301, in the first group 4 There are a second set of 4 corner points (321, 322, 323, and 324) outside the corner points, and a third set of 4 corner points (331, 332, 333, and 334) outside the second set of 4 corner points.
- the center point 301 and any one of the above three groups (ie, 4 corner points) or any two groups (ie, 8 corner points) or all three groups (ie, 12 corner points) may be selected as feature points.
- the set that is, the feature point set of one main positioning block can be 5, 9 or 13 feature points.
- a two-dimensional code has three main positioning blocks. If each main positioning block selects five feature points, there are 15 feature points. If each main positioning block selects 9 feature points, then there are a total of 27 feature points; if each feature block selects 13 feature points, there are 39 feature points. Need to explain, the above The same number of feature points are selected for each of the primary positioning blocks. In other embodiments, a different number of feature points may be selected for each primary positioning block, and details are not described herein again.
- the number of feature point sets can be selected according to actual conditions. The more feature points are selected, the more accurate the calculation result is, but the larger the calculation amount is; the less the feature points are selected, the smaller the calculation amount is, but the calculation result may be biased.
- FIG. 3B is a schematic diagram of selecting the largest number of feature point sets. Referring to FIG. 3B, 39 feature points are obtained in the entire two-dimensional code image, and the relative positions of the 39 feature points are fixed, that is, the 39 feature points can be uniquely determined.
- a center point of the main positioning block and a black and white pixel boundary edge center point may also be adopted as the feature point set.
- the following is an example of a main positioning block.
- 401 is the center point of the main positioning block.
- the center point 401 is used as a starting point, and the center point of the black and white pixel boundary edge is detected around the center point, and the center point 401 is closest to the center point 401.
- the center point of the black and white pixel boundary edge that can be acquired by one main positioning block can be 4, 8, or 12, and the center point, that is, the feature point set is 5, 9, or 13 feature points.
- the three main positioning blocks of a two-dimensional code can obtain 15, 27 or 39 feature points.
- the two-dimensional code is used as the Marker, and the position of the two-dimensional code can be effectively recognized by performing feature detection on the preset position of the main positioning block of the two-dimensional code.
- Step S106 determining spatial position information of the two-dimensional code in the image according to position information in the two-dimensional code.
- the preset standard position information is acquired, and the standard position information is matched with the position information in the two-dimensional code to obtain spatial position information of the two-dimensional code in the image (including spatial position parameters and rotation). parameter).
- the spatial position of the two-dimensional code can be continuously tracked.
- the spatial position of the obtained two-dimensional code can be applied to augmented reality technology, which will be described in detail below with reference to FIG.
- FIG. 5 is a flowchart of a two-dimensional code identification method according to another embodiment of the present application. As shown in FIG. 5, the method includes:
- Step S502 starting a camera device of the terminal device (for example, including a smart phone, a tablet computer, a digital camera, etc.), and capturing a real scene image containing the two-dimensional code.
- a camera device of the terminal device for example, including a smart phone, a tablet computer, a digital camera, etc.
- Step S504 scanning the two-dimensional code to extract a feature point set of the two-dimensional code, and the step of extracting the feature point set of the specific two-dimensional code may refer to the description of FIG. 3 or FIG. 4. If the feature point set extraction fails, step S502 is continued.
- step S506 internal parameters of the camera device, such as a focal length, an image center, and the like, are acquired.
- Step S508 point cloud registration, if successful, step S510 is performed, otherwise step S502 is performed.
- the preset standard position information is acquired, for example, the position of the front view of the two-dimensional code that can be captured by the camera as a standard position.
- the first point cloud data (such as a 3d point cloud) of the feature point set of the standard position can be obtained by combining the standard position information with the internal parameters of the pre-acquired camera device (for example, including the focal length, the image center, and the like).
- the second point cloud data of the feature point set of the two-dimensional code (such as a 3d point cloud) can be obtained.
- the point cloud registration is performed according to the first point cloud data and the two point cloud data, and the positional relationship between the first point cloud data and the two point cloud data is calculated, thereby obtaining spatial position information of the two-dimensional code in the image (ie, The spatial position of the camera).
- Step S510 updating the spatial position of the virtual object by using the spatial position of the camera, that is, completing the complete process of the augmented reality.
- the virtual object includes any one or a combination of text, picture, video, three-dimensional model, animation, sound, and geographic location information.
- FIG. 6 is a structural block diagram of a system for identifying a location of a two-dimensional code according to an embodiment of the present application. As shown in FIG. 6, the method includes:
- An obtaining module 610 configured to acquire a two-dimensional code in an image
- the identification module 620 is configured to perform feature detection according to the primary positioning block of the two-dimensional code, and identify location information in the two-dimensional code;
- the spatial location determining module 630 is configured to determine spatial location information of the two-dimensional code in the image according to location information in the two-dimensional code. Further, the spatial location determining module 630 is configured to: acquire preset standard location information, and match the standard location information with location information in the two-dimensional code to obtain the spatial location information.
- the tracking module 640 is configured to track location information in the two-dimensional code, and determine spatial location information of the two-dimensional code in the image according to the location information in the new two-dimensional code.
- the identification module 620 further includes:
- a first determining module 621 configured to determine one or more primary positioning blocks of the two-dimensional code
- the first obtaining module 622 is configured to acquire a central location point information and a plurality of corner location information of each primary positioning block, where the first acquiring module acquires 12, 8 or 4 of each primary positioning block. Corner location information.
- the first detecting module 623 is configured to perform feature detection by using the center point position information and the corner point position information of the acquired main positioning block as feature point sets.
- the identification module 620 further includes:
- a second determining module 626 configured to determine one or more primary positioning blocks of the two-dimensional code
- the second obtaining module 627 is configured to acquire a central point position information of each of the main positioning blocks and a plurality of black and white pixel boundary edge center point position information, where the second obtaining module acquires 12 of each main positioning block. 8 or 4 black and white pixel boundary edge center point position information.
- the second detecting module 628 is configured to perform feature detection on the acquired center point position information of the main positioning block and the black and white pixel boundary edge center point position information as a feature point set.
- FIG. 8 is a structural block diagram of a system for recognizing a location of a two-dimensional code for augmented reality technology according to an embodiment of the present application. As shown in FIG. 8, the method includes:
- the obtaining module 810 is configured to acquire a two-dimensional code in the image
- the identification module 820 is configured to perform feature detection according to the primary positioning block of the two-dimensional code, and identify location information in the two-dimensional code;
- the spatial location determining module 830 is configured to calculate spatial location information of the two-dimensional code in the image according to location information in the two-dimensional code.
- a virtual application data obtaining module 840 configured to acquire virtual application data corresponding to the two-dimensional code
- the virtual application data location update module 850 is configured to determine a spatial location of the virtual application data according to the spatial location information.
- the operation steps of the method of the present application correspond to the structural features of the system, and can be cross-referenced, no longer One by one.
- the present application recognizes the position of the two-dimensional code by using the two-dimensional code as the Marker and performing feature detection on the preset position of the main positioning block of the two-dimensional code.
- the feature point set of the extracted two-dimensional code has a fixed relative position, is unique, is not easy to be confused, and has a good tracking effect.
- the technical solution provided according to the present application is adapted to all QR codes without regenerating the preset feature point set each time.
- embodiments of the present application can be provided as a method, system, or computer program product.
- the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
- the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
- a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
- processors CPUs
- input/output interfaces network interfaces
- memory volatile and non-volatile memory
- the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
- RAM random access memory
- ROM read only memory
- Memory is an example of a computer readable medium.
- Computer readable media includes both permanent and non-persistent, removable and non-removable media.
- Information storage can be implemented by any method or technology.
- the information can be computer readable instructions, data structures, modules of programs, or other data.
- Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
- computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Toxicology (AREA)
- Electromagnetism (AREA)
- Health & Medical Sciences (AREA)
- Image Analysis (AREA)
- User Interface Of Digital Computer (AREA)
- Navigation (AREA)
- Aiming, Guidance, Guns With A Light Source, Armor, Camouflage, And Targets (AREA)
Abstract
Description
Claims (18)
- 一种识别二维码位置的方法,其特征在于,包括:获取图像中的二维码;根据所述二维码的主定位块进行特征检测,识别所述二维码中的位置信息;根据所述二维码中的位置信息确定所述二维码在所述图像中的空间位置信息。
- 根据权利要求1所述的方法,其特征在于,还包括:跟踪所述二维码中的位置信息。
- 根据权利要求1所述的方法,其特征在于,所述根据所述二维码的主定位块进行特征检测的步骤,包括:确定所述二维码的一个或多个主定位块;分别获取每个主定位块的一中心点位置信息及多个角点位置信息;将获取的主定位块的中心点位置信息和角点位置信息作为特征点集,进行特征检测。
- 根据权利要求2所述的方法,其特征在于,获取每个主定位块的12、8或4个角点位置信息。
- 根据权利要求1所述的方法,其特征在于,所述根据所述二维码的主定位块进行特征检测的步骤,包括:确定所述二维码的一个或多个主定位块;分别获取每个主定位块的一中心点位置信息及多个黑白像素交界边缘中心点位置信息;将获取的主定位块的中心点位置信息和黑白像素交界边缘中心点位置信息作为特征点集,进行特征检测。
- 根据权利要求5所述的方法,其特征在于,获取每个主定位块的12、8或4个黑白交界边缘中心点位置信息。
- 根据权利要求1所述的方法,其特征在于,所述根据所述二维码中的位置信息确定所述二维码在所述图像中的空间位置信息的步骤,包括:获取预置的标准位置信息;将所述标准位置信息与所述二维码中的位置信息进行匹配,得到所述空间位置信息。
- 根据权利要求1所述的方法,其特征在于,所述二维码为快速反应QR二维码。
- 根据权利要求1至8中任一项所述的方法,其特征在于,还包括:获取与所述二维码对应的虚拟应用数据;根据所述空间位置信息确定所述虚拟应用数据的空间位置。
- 一种识别二维码位置的***,其特征在于,包括:获取模块,用于获取图像中的二维码;识别模块,用于根据所述二维码的主定位块进行特征检测,识别所述二维码中的位置信息;空间位置确定模块,用于根据所述二维码中的位置信息确定所述二维码在所述图像中的空间位置信息。
- 根据权利要求10所述的***,其特征在于,还包括:跟踪模块,用于跟踪所述二维码中的位置信息。
- 根据权利要求10所述的***,其特征在于,所述识别模块包括:第一确定模块,用于确定所述二维码的一个或多个主定位块;第一获取模块,用于分别获取每个主定位块的一中心位置点信息及多个 角点位置信息;第一检测模块,用于将获取的主定位块的中心点位置信息和角点位置信息作为特征点集,进行特征检测。
- 根据权利要求12所述的***,其特征在于,所述第一获取模块获取每个主定位块的12、8或4个角点位置信息。
- 根据权利要求10所述的***,其特征在于,所述识别模块包括:第二确定模块,用于确定所述二维码的一个或多个主定位块;第二获取模块,用于分别获取每个主定位块的一中心点位置信息及多个黑白像素交界边缘中心点位置信息;第二检测模块,用于将获取的主定位块的中心点位置信息和黑白像素交界边缘中心点位置信息作为特征点集,进行特征检测。
- 根据权利要求14所述的***,其特征在于,所述第二获取模块获取每个主定位块的12、8或4个黑白像素交界边缘中心点位置信息。
- 根据权利要求10所述的***,其特征在于,所述空间位置确定模块用于:获取预置的标准位置信息,将所述标准位置信息与所述二维码中的位置信息进行匹配,得到所述空间位置信息。
- 根据权利要求10所述的***,其特征在于,所述二维码为快速反应QR二维码。
- 根据权利要求10至17中任一项所述的***,其特征在于,还包括:虚拟应用数据获取模块,用于获取与所述二维码对应的虚拟应用数据;虚拟应用数据位置确定模块,用于根据所述空间位置信息确定所述虚拟应用数据的空间位置。
Priority Applications (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
SG11201900444XA SG11201900444XA (en) | 2016-07-22 | 2017-07-18 | Method and system for recognizing location information in two-dimensional code |
KR1020197005252A KR102104219B1 (ko) | 2016-07-22 | 2017-07-18 | 2차원 코드 내 위치 정보를 인지하기 위한 방법 및 시스템 |
JP2019503329A JP6936306B2 (ja) | 2016-07-22 | 2017-07-18 | 2次元コードの位置情報を認識する方法及びシステム |
EP17830462.2A EP3489856B1 (en) | 2016-07-22 | 2017-07-18 | Method and system for recognizing location information in two-dimensional code |
MYPI2019000141A MY193939A (en) | 2016-07-22 | 2017-07-18 | Method and system for recognizing location information in two-dimensional code |
US16/252,138 US10685201B2 (en) | 2016-07-22 | 2019-01-18 | Method and system for recognizing location information in two-dimensional code |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610584889.1A CN106897648B (zh) | 2016-07-22 | 2016-07-22 | 识别二维码位置的方法及其*** |
CN201610584889.1 | 2016-07-22 |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US16/252,138 Continuation US10685201B2 (en) | 2016-07-22 | 2019-01-18 | Method and system for recognizing location information in two-dimensional code |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2018014828A1 true WO2018014828A1 (zh) | 2018-01-25 |
Family
ID=59190965
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2017/093370 WO2018014828A1 (zh) | 2016-07-22 | 2017-07-18 | 识别二维码位置的方法及其*** |
Country Status (9)
Country | Link |
---|---|
US (1) | US10685201B2 (zh) |
EP (1) | EP3489856B1 (zh) |
JP (1) | JP6936306B2 (zh) |
KR (1) | KR102104219B1 (zh) |
CN (2) | CN106897648B (zh) |
MY (1) | MY193939A (zh) |
SG (1) | SG11201900444XA (zh) |
TW (1) | TWI683257B (zh) |
WO (1) | WO2018014828A1 (zh) |
Families Citing this family (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106897648B (zh) | 2016-07-22 | 2020-01-31 | 阿里巴巴集团控股有限公司 | 识别二维码位置的方法及其*** |
CN107689061A (zh) * | 2017-07-11 | 2018-02-13 | 西北工业大学 | 用于室内移动机器人定位的规则图形码及定位方法 |
CN112861560B (zh) * | 2017-09-27 | 2023-12-22 | 创新先进技术有限公司 | 二维码定位方法及装置 |
CN107895138B (zh) * | 2017-10-13 | 2020-06-23 | 西安艾润物联网技术服务有限责任公司 | 空间障碍物检测方法、装置及计算机可读存储介质 |
CN108629220A (zh) * | 2018-03-23 | 2018-10-09 | 阿里巴巴集团控股有限公司 | 一种二维码识读方法、装置及设备 |
CN108960384B (zh) * | 2018-06-07 | 2020-04-28 | 阿里巴巴集团控股有限公司 | 一种图形码的解码方法及客户端 |
CN111507119B (zh) * | 2019-01-31 | 2024-02-06 | 北京骑胜科技有限公司 | 标识码识别方法、装置、电子设备及计算机可读存储介质 |
US10854016B1 (en) * | 2019-06-20 | 2020-12-01 | Procore Technologies, Inc. | Computer system and method for creating an augmented environment using QR tape |
CN110481602B (zh) * | 2019-07-15 | 2021-06-25 | 广西柳钢东信科技有限公司 | 一种轨道运输设备的实时定位方法及装置 |
CN110539307A (zh) * | 2019-09-09 | 2019-12-06 | 北京极智嘉科技有限公司 | 机器人、机器人定位方法、定位导航***及定位标记 |
CN110852132B (zh) * | 2019-11-15 | 2023-10-03 | 北京金山数字娱乐科技有限公司 | 一种二维码空间位置确认方法及装置 |
WO2022032680A1 (zh) * | 2020-08-14 | 2022-02-17 | 深圳传音控股股份有限公司 | 操作方法、终端及计算机存储介质 |
CN112560606B (zh) * | 2020-12-02 | 2024-04-16 | 北京经纬恒润科技股份有限公司 | 挂车角度识别方法及装置 |
CN113384361B (zh) * | 2021-05-21 | 2022-10-28 | 中山大学 | 一种视觉定位方法、***、装置及存储介质 |
CN113377351B (zh) * | 2021-07-05 | 2022-05-17 | 重庆市规划和自然资源信息中心 | 用于大规模政务业务的模型构建工作*** |
CN113935909B (zh) * | 2021-09-22 | 2024-07-05 | 南方电网数字平台科技(广东)有限公司 | 一种二维码校正识别方法及装置 |
CN115578606B (zh) * | 2022-12-07 | 2023-03-31 | 深圳思谋信息科技有限公司 | 二维码识别方法、装置、计算机设备及可读存储介质 |
CN115630663A (zh) * | 2022-12-19 | 2023-01-20 | 成都爱旗科技有限公司 | 一种二维码识别方法、装置及电子设备 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103049728A (zh) * | 2012-12-30 | 2013-04-17 | 成都理想境界科技有限公司 | 基于二维码的增强现实方法、***及终端 |
CN103971079A (zh) * | 2013-01-28 | 2014-08-06 | 腾讯科技(深圳)有限公司 | 一种二维码的增强现实实现方法和装置 |
CN104809422A (zh) * | 2015-04-27 | 2015-07-29 | 江苏中科贯微自动化科技有限公司 | 基于图像处理的qr码识别方法 |
US20150278573A1 (en) * | 2012-07-23 | 2015-10-01 | Korea Advanced Institute Of Science And Technology | Method of recognizing qr code in image data and apparatus and method for converting qr code in content data into touchable object |
CN106897648A (zh) * | 2016-07-22 | 2017-06-27 | 阿里巴巴集团控股有限公司 | 识别二维码位置的方法及其*** |
Family Cites Families (35)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2835274B2 (ja) | 1994-02-24 | 1998-12-14 | 株式会社テック | 画像認識装置 |
US6073846A (en) | 1994-08-17 | 2000-06-13 | Metrologic Instruments, Inc. | Holographic laser scanning system and process and apparatus and method |
US6416154B1 (en) | 1997-07-12 | 2002-07-09 | Silverbrook Research Pty Ltd | Printing cartridge with two dimensional code identification |
US6377710B1 (en) * | 1998-11-25 | 2002-04-23 | Xerox Corporation | Method and apparatus for extracting the skeleton of a binary figure by contour-based erosion |
JP3458737B2 (ja) | 1998-11-27 | 2003-10-20 | 株式会社デンソー | 2次元コードの読取方法及び記録媒体 |
DE60118051T2 (de) | 2000-04-06 | 2006-08-31 | Seiko Epson Corp. | Verfahren und Vorrichtung zum Lesen von einem zwei-dimensionalen Strichkode und Datenspeichermedium |
US6959866B2 (en) * | 2002-05-30 | 2005-11-01 | Ricoh Company, Ltd. | 2-Dimensional code pattern, 2-dimensional code pattern supporting medium, 2-dimensional code pattern generating method, and 2-dimensional code reading apparatus and method |
JP3516144B1 (ja) | 2002-06-18 | 2004-04-05 | オムロン株式会社 | 光学情報コードの読取方法および光学情報コード読取装置 |
JP4301775B2 (ja) | 2002-07-18 | 2009-07-22 | シャープ株式会社 | 2次元コード読み取り装置,2次元コード読み取り方法,2次元コード読み取りプログラム及び該プログラムの記録媒体 |
JP3996520B2 (ja) | 2003-01-30 | 2007-10-24 | 株式会社デンソーウェーブ | 二次元情報コードおよびその生成方法 |
JP4180497B2 (ja) | 2003-12-05 | 2008-11-12 | 富士通株式会社 | コード種類判別方法、およびコード境界検出方法 |
US7751629B2 (en) | 2004-11-05 | 2010-07-06 | Colorzip Media, Inc. | Method and apparatus for decoding mixed code |
JP4810918B2 (ja) | 2005-08-01 | 2011-11-09 | 富士ゼロックス株式会社 | コードパターン画像生成装置及び方法、コードパターン画像読取装置及び方法、及びコードパターン画像媒体 |
KR100828539B1 (ko) * | 2005-09-20 | 2008-05-13 | 후지제롯쿠스 가부시끼가이샤 | 이차원 코드의 검출 방법, 검출 장치, 및 검출 프로그램을기억한 기억 매체 |
JP2007090448A (ja) * | 2005-09-27 | 2007-04-12 | Honda Motor Co Ltd | 二次元コード検出装置及びそのプログラム、並びに、ロボット制御情報生成装置及びロボット |
JP4911340B2 (ja) | 2006-02-10 | 2012-04-04 | 富士ゼロックス株式会社 | 二次元コード検出システムおよび二次元コード検出プログラム |
US8532299B2 (en) * | 2007-05-29 | 2013-09-10 | Denso Wave Incorporated | Method for producing two-dimensional code and reader for reading the two-dimensional code |
JP4956375B2 (ja) | 2007-10-30 | 2012-06-20 | キヤノン株式会社 | 画像処理装置、画像処理方法 |
CN101615259B (zh) | 2008-08-01 | 2013-04-03 | 凌通科技股份有限公司 | 一种二维光学辨识码的识别*** |
US20110290882A1 (en) * | 2010-05-28 | 2011-12-01 | Microsoft Corporation | Qr code detection |
CN101908125B (zh) * | 2010-06-01 | 2014-07-02 | 福建新大陆电脑股份有限公司 | Qr码条码解码芯片及其解码方法 |
KR101334049B1 (ko) * | 2011-03-16 | 2013-11-28 | 성준형 | 증강 현실 기반 사용자 인터페이스 제공 장치 및 방법 |
CN103582893B (zh) * | 2011-06-08 | 2017-10-13 | 英派尔科技开发有限公司 | 用于增强现实表示的二维图像获取 |
CN103049729B (zh) * | 2012-12-30 | 2015-12-23 | 成都理想境界科技有限公司 | 基于二维码的增强现实方法、***及终端 |
US20140210857A1 (en) * | 2013-01-28 | 2014-07-31 | Tencent Technology (Shenzhen) Company Limited | Realization method and device for two-dimensional code augmented reality |
JP5967000B2 (ja) * | 2013-03-29 | 2016-08-10 | 株式会社デンソーウェーブ | 情報コード読取システム、情報コード読取装置、情報コード |
CN104517108B (zh) * | 2013-09-29 | 2017-12-22 | 北大方正集团有限公司 | 一种确定qr码二值化图像边缘线的方法及*** |
CN103632384B (zh) * | 2013-10-25 | 2016-06-01 | 大连理工大学 | 组合式标记点及标记点中心的快速提取方法 |
WO2015067725A1 (en) * | 2013-11-07 | 2015-05-14 | Scantrust Sa | Two dimensional barcode and method of authentication of such barcode |
JP2015191531A (ja) * | 2014-03-28 | 2015-11-02 | 株式会社トッパンTdkレーベル | 2次元コードの空間位置の決定方法及びそのための装置 |
CN104008359B (zh) * | 2014-04-18 | 2017-04-12 | 杭州晟元数据安全技术股份有限公司 | 一种用于qr码识别的精确网格采样方法 |
WO2015174191A1 (ja) * | 2014-05-14 | 2015-11-19 | 共同印刷株式会社 | 二次元コード、二次元コードの解析システム |
KR101770540B1 (ko) * | 2014-05-14 | 2017-08-22 | 교도 인사쯔 가부시키가이샤 | 이차원 코드, 이차원 코드의 해석 시스템 및 이차원 코드의 작성 시스템 |
CN104268498B (zh) * | 2014-09-29 | 2017-09-19 | 杭州华为数字技术有限公司 | 一种二维码的识别方法及终端 |
CN104951726B (zh) * | 2015-06-25 | 2017-12-08 | 福建联迪商用设备有限公司 | 用于qr二维码位置探测的方法及装置 |
-
2016
- 2016-07-22 CN CN201610584889.1A patent/CN106897648B/zh active Active
- 2016-07-22 CN CN202010095707.0A patent/CN111291584B/zh active Active
-
2017
- 2017-06-09 TW TW106119329A patent/TWI683257B/zh active
- 2017-07-18 SG SG11201900444XA patent/SG11201900444XA/en unknown
- 2017-07-18 JP JP2019503329A patent/JP6936306B2/ja active Active
- 2017-07-18 KR KR1020197005252A patent/KR102104219B1/ko active IP Right Grant
- 2017-07-18 WO PCT/CN2017/093370 patent/WO2018014828A1/zh unknown
- 2017-07-18 EP EP17830462.2A patent/EP3489856B1/en active Active
- 2017-07-18 MY MYPI2019000141A patent/MY193939A/en unknown
-
2019
- 2019-01-18 US US16/252,138 patent/US10685201B2/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150278573A1 (en) * | 2012-07-23 | 2015-10-01 | Korea Advanced Institute Of Science And Technology | Method of recognizing qr code in image data and apparatus and method for converting qr code in content data into touchable object |
CN103049728A (zh) * | 2012-12-30 | 2013-04-17 | 成都理想境界科技有限公司 | 基于二维码的增强现实方法、***及终端 |
CN103971079A (zh) * | 2013-01-28 | 2014-08-06 | 腾讯科技(深圳)有限公司 | 一种二维码的增强现实实现方法和装置 |
CN104809422A (zh) * | 2015-04-27 | 2015-07-29 | 江苏中科贯微自动化科技有限公司 | 基于图像处理的qr码识别方法 |
CN106897648A (zh) * | 2016-07-22 | 2017-06-27 | 阿里巴巴集团控股有限公司 | 识别二维码位置的方法及其*** |
Non-Patent Citations (1)
Title |
---|
See also references of EP3489856A4 * |
Also Published As
Publication number | Publication date |
---|---|
JP6936306B2 (ja) | 2021-09-15 |
TWI683257B (zh) | 2020-01-21 |
US10685201B2 (en) | 2020-06-16 |
SG11201900444XA (en) | 2019-02-27 |
CN111291584A (zh) | 2020-06-16 |
KR20190032501A (ko) | 2019-03-27 |
EP3489856A4 (en) | 2020-03-04 |
TW201804373A (zh) | 2018-02-01 |
CN106897648A (zh) | 2017-06-27 |
EP3489856B1 (en) | 2022-04-06 |
EP3489856A1 (en) | 2019-05-29 |
MY193939A (en) | 2022-11-02 |
KR102104219B1 (ko) | 2020-04-24 |
CN111291584B (zh) | 2023-05-02 |
CN106897648B (zh) | 2020-01-31 |
JP2019523500A (ja) | 2019-08-22 |
US20190156092A1 (en) | 2019-05-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2018014828A1 (zh) | 识别二维码位置的方法及其*** | |
US20200279121A1 (en) | Method and system for determining at least one property related to at least part of a real environment | |
WO2019218824A1 (zh) | 一种移动轨迹获取方法及其设备、存储介质、终端 | |
CN107392958B (zh) | 一种基于双目立体摄像机确定物体体积的方法及装置 | |
EP2711670B1 (en) | Visual localisation | |
Chen et al. | City-scale landmark identification on mobile devices | |
JP5950973B2 (ja) | フレームを選択する方法、装置、及びシステム | |
Gao et al. | Robust RGB-D simultaneous localization and mapping using planar point features | |
WO2018210047A1 (zh) | 数据处理方法、数据处理装置、电子设备及存储介质 | |
CN106485186B (zh) | 图像特征提取方法、装置、终端设备及*** | |
CN112435338B (zh) | 电子地图的兴趣点的位置获取方法、装置及电子设备 | |
CN110363179B (zh) | 地图获取方法、装置、电子设备以及存储介质 | |
CN112102404B (zh) | 物体检测追踪方法、装置及头戴显示设备 | |
CN110443228B (zh) | 一种行人匹配方法、装置、电子设备及存储介质 | |
Tomono | Loop detection for 3D LiDAR SLAM using segment-group matching | |
JP2022519398A (ja) | 画像処理方法、装置及び電子機器 | |
CN113298871B (zh) | 地图生成方法、定位方法及其***、计算机可读存储介质 | |
Bae et al. | Fast and scalable 3D cyber-physical modeling for high-precision mobile augmented reality systems | |
JP2018120320A (ja) | 画像処理装置,画像処理方法,画像処理プログラム | |
Pereira et al. | Mirar: Mobile image recognition based augmented reality framework | |
Amato et al. | Technologies for visual localization and augmented reality in smart cities | |
CN105930813B (zh) | 一种在任意自然场景下检测行文本的方法 | |
Choi et al. | Smart Booklet: Tour guide system with mobile augmented reality | |
Park et al. | Real‐time robust 3D object tracking and estimation for surveillance system | |
US20220414998A1 (en) | Augmenting a first image with a second image |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 17830462 Country of ref document: EP Kind code of ref document: A1 |
|
ENP | Entry into the national phase |
Ref document number: 2019503329 Country of ref document: JP Kind code of ref document: A |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
ENP | Entry into the national phase |
Ref document number: 20197005252 Country of ref document: KR Kind code of ref document: A |
|
ENP | Entry into the national phase |
Ref document number: 2017830462 Country of ref document: EP Effective date: 20190222 |