CN112364732A - Image processing method and apparatus, storage medium, and electronic apparatus - Google Patents
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Abstract
The invention provides an image processing method and device, a storage medium and an electronic device, comprising: acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on image acquisition equipment, and the group of image data comprises long frame data and short frame data; uploading the long frame data to a first image processor so as to identify a character object in one frame of image through the first image processor; uploading the short frame data to a second image processor to identify the vehicle object in one frame of image through the second image processor; the person object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor are acquired. The invention solves the problems of high cost and resource waste caused by the fact that the same monitoring camera cannot monitor all objects in a monitoring scene and a plurality of monitoring cameras need to be arranged in the monitoring scene.
Description
Technical Field
The present invention relates to the field of image processing, and in particular, to an image processing method and apparatus, a storage medium, and an electronic apparatus.
Background
The current security monitoring camera has gradually been expanding the application of intelligent snapshot function, such as people's bayonet, car bayonet etc.. Because the emphasis on monitoring people and vehicles is different, even contradictory, such as when the brightness of human face is appropriate, the license plate may be overexposed and have smear. If the user wants to preview the interface presentation at the vehicle entrance, the human face is likely to be too dark. If the person is in the mouth, the license plate is likely to be overexposed.
In the prior art, a plurality of monitoring cameras are usually arranged and respectively monitor different contents, for example, one monitoring camera is used for monitoring people, and the other monitoring camera is used for monitoring vehicles. In this way, a plurality of monitoring cameras need to be arranged, and the cost is high.
In the related art, an effective solution is not available at present for the problems of high cost and resource waste caused by the fact that the same monitoring camera cannot monitor all objects in a monitoring scene and a plurality of monitoring cameras need to be arranged in the monitoring scene.
Disclosure of Invention
The embodiment of the invention provides an image processing method and device, a storage medium and an electronic device, which are used for at least solving the problems of high cost and resource waste caused by the fact that the same monitoring camera cannot monitor all objects in a monitoring scene and a plurality of monitoring cameras need to be arranged in the monitoring scene in the related technology.
According to an embodiment of the present invention, there is provided an image processing method including: acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on an image acquisition device, and the group of image data comprises long frame data and short frame data; uploading the long frame data to a first image processor to identify a character object in the frame of image through the first image processor; uploading the short frame data to a second image processor to identify a vehicle object in the one frame image by the second image processor; and acquiring a character object recognition result output by the first image processor and a vehicle object recognition result output by the second image processor.
Optionally, uploading the long frame data to a first image processor to identify the human object in the frame of image by the first image processor, comprising: uploading the long frame data to a first image processor; the first image processor adjusts the frame of image according to the exposure duration of the character object in the frame of image and a first adjustment parameter to obtain a first image; the first image processor identifies the person objects in the first image and the number of the person objects, wherein the person object identification result comprises the person objects in the first image and the number of the person objects.
Optionally, uploading the short frame data to a second image processor to identify the vehicle object in the frame of image by the second image processor, comprising: uploading the short frame data to a second image processor; the second image processor adjusts the frame of image according to a second adjustment parameter and the exposure duration of the vehicle object in the frame of image to obtain a second image; the second image processor identifies the vehicle object in the second image and the number of the vehicle objects, wherein the vehicle object identification result comprises the vehicle object in the first image and the number of the vehicle objects.
Optionally, the method further comprises: and uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the character object in the frame image and the exposure duration of the vehicle object in the frame image to obtain a third image.
Optionally, the uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the person object in the frame image and the exposure duration of the vehicle object in the frame image, to obtain a third image, includes: the third image processor acquires a first adjusting parameter when the first image processor adjusts the frame of image and a second adjusting parameter when the second image processor adjusts the frame of image; the third image processor determines the third adjustment parameter according to the first adjustment parameter and the second adjustment parameter, wherein the third adjustment parameter is between the first adjustment parameter and the second adjustment parameter; and the third image processor adjusts the frame of image according to the third adjustment parameter to obtain the third image.
Optionally, the method further comprises: in a case where it is determined that the number of the human objects in the one frame image is larger than a first threshold value and the number of the vehicle objects is smaller than a second threshold value, displaying a human object recognition result output by the first image processor; in a case where it is determined that the number of the human objects in the one frame image is smaller than a first threshold and the number of the vehicle objects is larger than a second threshold, displaying a vehicle object recognition result output by the second image processor; and displaying a third image output by a third image processor in the case where it is determined that the number of the human objects in the one frame image is greater than a first threshold and the number of the vehicle objects is greater than a second threshold.
According to another embodiment of the present invention, there is provided an image processing apparatus including: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, the wide dynamic sensor is arranged on image acquisition equipment, and the group of image data comprises long frame data and short frame data; a first uploading module, configured to upload the long frame data to a first image processor, so as to identify a person object in the frame of image through the first image processor; a second uploading module, configured to upload the short frame data to a second image processor, so as to identify, by the second image processor, a vehicle object in the frame of image; and the second acquisition module is used for acquiring the character object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor.
According to another embodiment of the present invention, there is provided an image processing system including: the image processing device comprises a first image processor, a second image processor and a processing unit, wherein the first image processor is used for acquiring long frame data of one frame of image acquired by a wide dynamic sensor and identifying a character object in the one frame of image through the long frame data; the second image processor is used for acquiring short frame data of one frame of image acquired by the wide dynamic sensor, and identifying the vehicle object in the one frame of image through the short frame data; and the third image processor is used for determining a third adjustment parameter according to the first adjustment parameter when the first image processor adjusts the frame of image and the second adjustment parameter when the second image processor adjusts the frame of image, and adjusting the frame of image according to the third adjustment parameter to obtain a third image.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, a group of image data of one frame of image acquired by the wide dynamic sensor is acquired, wherein the wide dynamic sensor is arranged on the image acquisition equipment, and the group of image data comprises long frame data and short frame data; uploading the long frame data to a first image processor so as to identify the character object in the frame image through the first image processor; uploading the short frame data to a second image processor to identify the vehicle object in the frame of image through the second image processor; the person object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor are acquired. The purpose that the person object and the vehicle object in one frame of image are recognized by the first image processor and the second image processor respectively and one frame of image collected by one image collecting device can be processed is achieved. Therefore, the problems of high cost and resource waste caused by the fact that the same monitoring camera cannot monitor all objects in a monitoring scene and a plurality of monitoring cameras need to be arranged in the monitoring scene in the related technology can be solved, and the effects of improving monitoring accuracy and saving resources can be achieved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a mobile terminal according to an application program upgrading method of an embodiment of the present invention;
FIG. 2 is a flow chart of an image processing method according to an embodiment of the present invention;
FIG. 3 is an image processing architecture diagram according to an embodiment of the present invention;
fig. 4 is a block diagram of the structure of an image processing apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the mobile terminal as an example, fig. 1 is a block diagram of a hardware structure of the mobile terminal of an image processing method according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal 10 may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally may also include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of an application software and a module, such as a computer program corresponding to the image processing method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In the present embodiment, an image processing method operating in the mobile terminal is provided, and fig. 2 is a flowchart of image processing according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:
step S202, acquiring a group of image data of a frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on an image acquisition device, and the group of image data comprises long frame data and short frame data;
step S204, uploading the long frame data to a first image processor so as to identify a character object in the frame image through the first image processor;
step S206, uploading the short frame data to a second image processor so as to identify the vehicle object in the frame image through the second image processor;
step S208, the character object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor are obtained.
As an optional embodiment, the image capturing device may be a surveillance camera, the surveillance camera is a single sensor device, a frame of image is captured by a wide dynamic sensor, binary data output by the sensor is a set of image data of the frame of image, and the set of image data output by the sensor includes long frame data raw _ L and short frame data raw _ S.
As an optional implementation, the data output by the sensor may be divided according to the exposure duration of one frame of image, and the image data with the exposure duration greater than or equal to the preset threshold is used as the long frame data, and the image data with the exposure duration less than the preset threshold is used as the short frame data. Because the data output by the sensor is divided according to the exposure duration, the image can be processed in different exposure processing modes. For example, since the exposure time of the long frame data is relatively long, an image processing mode of reducing the exposure can be adopted, and the face exposure effect in the image result which can be output is better. Because the exposure time of the short frame data is lower, an image processing mode of increasing exposure can be adopted, and the exposure effect of the license plate in the image result which can be output is better.
As an alternative implementation, FIG. 3 is a diagram of an image processing architecture according to an embodiment of the present invention. In fig. 3, a set of image data of a frame of acquired image is output by a sensor, long frame data raw _ L in the set of image data is sent to a first image processor ISP1, the first image processor mainly performs face capture and face recognition, and the ISP1 performs linear image processing on the long frame data, wherein a specific image linear processing mode may refer to an image processing mode of a face in the prior art. So that the image included in the first image processing result output by the first image processor ISP1 can accurately recognize the face of a person.
And sending short frame data raw _ S in the group of image data to a second image processor ISP2, wherein the second image processor mainly performs license plate capture and license plate recognition, and the ISP2 performs image processing on the segment frame data, and the specific image processing mode can refer to the image processing mode of the license plate in the prior art. So that the image included in the second image processing result output by the second image processor ISP2 can accurately recognize the license plate.
Through the steps, a group of image data of one frame of image acquired by the wide dynamic sensor is acquired, wherein the wide dynamic sensor is arranged on the image acquisition equipment, and the group of image data comprises long frame data and short frame data; uploading the long frame data to a first image processor so as to identify the character object in the frame image through the first image processor; uploading the short frame data to a second image processor to identify the vehicle object in the frame of image through the second image processor; the person object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor are acquired. The purpose that the person object and the vehicle object in one frame of image are recognized by the first image processor and the second image processor respectively and one frame of image collected by one image collecting device can be processed is achieved. Therefore, the problems of high cost and resource waste caused by the fact that the same monitoring camera cannot monitor all objects in a monitoring scene and a plurality of monitoring cameras need to be arranged in the monitoring scene in the related technology can be solved, and the effects of improving monitoring accuracy and saving resources can be achieved.
Alternatively, the execution subject of the above steps may be a terminal or the like, but is not limited thereto.
As an alternative embodiment, uploading the long frame data to a first image processor to identify a human object in the frame of image by the first image processor, includes: uploading the long frame data to a first image processor; the first image processor adjusts the frame of image according to the exposure duration of the character object in the frame of image and a first adjustment parameter to obtain a first image; the first image processor identifies the person objects in the first image and the number of the person objects, wherein the person object identification result comprises the person objects in the first image and the number of the person objects. In this embodiment, the first image processor may adjust the image according to an exposure time of the human object in the image. For example, if the exposure time of the human object in the image is too long, the exposure time may be adaptively adjusted so that the exposure time of the human object in the image is within a reasonable range. Specifically, a threshold range may be preset, and if the exposure duration of the person object in the image exceeds the threshold range, the exposure duration of the image is decreased so that the exposure duration of the person object in the image satisfies the threshold range, and the obtained person object in the first image may perform face recognition.
As an alternative embodiment, uploading the short frame data to a second image processor to identify the vehicle object in the frame of image by the second image processor, includes: uploading the short frame data to a second image processor; the second image processor adjusts the frame of image according to a second adjustment parameter and the exposure duration of the vehicle object in the frame of image to obtain a second image; the second image processor identifies the vehicle object in the second image and the number of the vehicle objects, wherein the vehicle object identification result comprises the vehicle object in the first image and the number of the vehicle objects. In this embodiment, the second image processor may adjust the image according to an exposure time period of the vehicle object in the image. For example, if the exposure time of the vehicle object in the image is too short, the exposure time may be adaptively adjusted so that the exposure time of the vehicle object in the image is within a reasonable range. Specifically, a threshold range may be preset, and if the exposure duration of the vehicle object in the image is smaller than the threshold range, the exposure duration of the image is increased so that the exposure duration of the vehicle object in the image satisfies the threshold range, and the vehicle object in the obtained second image may perform license plate recognition.
As an optional embodiment, the method further comprises: and uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the character object in the frame image and the exposure duration of the vehicle object in the frame image to obtain a third image. In this embodiment, as shown in fig. 3, the long frame data raw _ L and the short frame data raw _ S are transmitted to the third image processor ISP0, and image processing is performed. The third image processor may adjust the image according to an exposure time period of the human object in the image and an exposure time period of the vehicle. For example, in one frame of image, if the exposure duration of the person is too high and the exposure duration of the vehicle is too low, a value may be selected between the exposure duration of the person and the exposure of the vehicle as a third adjustment parameter, and the image may be processed using the third adjustment parameter to obtain a third image. Optionally, the first image processor and the second image processor perform automatic exposure, adjustment of exposure time and gain and aperture, and automatic white balance and other image processing, according to the requirements of the capture. The first image processing result comprises a first shutter shut1 and a first gain1 obtained in the process of recognizing the face in the image, and the second image processing result comprises a second shutter shut2 and a second gain2 obtained in the process of recognizing the license plate in the image. In this embodiment, the third image processor synthesizes raw _ L and raw _ S according to the ratio of shut1 and gain1 to shut2 and gain2, which can be referred to a conventional wide dynamic synthesis algorithm. Because the exposure of the long and short frames is controlled by the 1 route and the 2 route, the exposure control is not carried out on the 0 route, but other image processing can be carried out according to the requirement of a preview image, and the image obtained by debugging can be presented on a preview interface.
As an optional embodiment, the uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the person object in the frame image and the exposure duration of the vehicle object in the frame image, to obtain a third image, includes: the third image processor acquires a first adjusting parameter when the first image processor adjusts the frame of image and a second adjusting parameter when the second image processor adjusts the frame of image; the third image processor determines the third adjustment parameter according to the first adjustment parameter and the second adjustment parameter, wherein the third adjustment parameter is between the first adjustment parameter and the second adjustment parameter; and the third image processor adjusts the frame of image according to the third adjustment parameter to obtain the third image. In this embodiment, the third image processor may process the image according to the first adjustment parameter obtained in the process of processing the long frame data by the first image processor and the second adjustment parameter obtained in the process of processing the short frame data by the second image processor, so as to obtain the debugged image. Specifically, the third image processor may determine a third adjustment parameter according to the first adjustment parameter and the second adjustment parameter, where the third adjustment parameter may be a numerical value between the first adjustment parameter and the second adjustment parameter, and the third image processor processes the image using the third adjustment parameter to obtain a third image.
As an optional embodiment, the method further comprises: in a case where it is determined that the number of the human objects in the one frame image is larger than a first threshold value and the number of the vehicle objects is smaller than a second threshold value, displaying a human object recognition result output by the first image processor; in a case where it is determined that the number of the human objects in the one frame image is smaller than a first threshold and the number of the vehicle objects is larger than a second threshold, displaying a vehicle object recognition result output by the second image processor; and displaying a third image output by a third image processor in the case where it is determined that the number of the human objects in the one frame image is greater than a first threshold and the number of the vehicle objects is greater than a second threshold. In this embodiment, based on the original usage of the long frame and the short frame, a new usage scenario based on the long frame, the medium frame, and the short frame is added, wherein the third image output by the third image processor is the medium frame image. In the display of the web preview side, the output of the medium frame may be defaulted as the output of the screen. The corresponding images may also be output and displayed according to the number of human objects and vehicle objects in the image. When there are more person objects and fewer vehicle objects in the image, the person object recognition result output by the first image processor may be displayed. The vehicle recognition result output by the second image processor may be displayed when there are fewer character objects and more vehicle objects in the image. The third image output by the third image processor may be displayed when the number of the human object and the vehicle object in the image is equivalent. Specifically, the first threshold and the second threshold may be preset by setting a threshold, the specific value may be determined according to actual conditions, and the first threshold and the second threshold may be equal or different. For example, the first image processor outputs long frames for intelligent face analysis and counts the number of face frames a. And outputting short frames of the second image processor for intelligently analyzing the moving vehicle, and counting the number B of vehicle frames. If A and B are less than 3 respectively, the picture of the web end is displayed by using the middle frame picture output by the third image processor. If A and B are respectively larger than 3, the picture of the web end is displayed by using a wide dynamic picture with long frames fused with short frames. If A is more than 3 and B is less than 3, the picture of the web end is displayed by using the wide dynamic picture of the frame in the long frame fusion. If B is more than 3 and A is less than 3, the pictures of the web end are displayed by using the wide dynamic pictures of the frames in the short frame fusion. Although three frames are output, the three paths of ISP are corresponding, one path is used for long frames, the other path is used for short frames, and the other path is used for display output.
According to the method, the data of the preview interface and the intelligent snapshot are separated, so that the data of the preview and the intelligent snapshot are respectively debugged, the requirement of intelligent analysis is met, and the requirements of moderate brightness and more details in the process of viewing the preview interface can be met. The camera with a single sensor can realize the output and the function of three sensors, so that the camera has stronger function. One camera can be used as three cameras, so that the effects of reducing expenditure and saving resources can be achieved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, an image processing apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description of the apparatus is omitted for brevity. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of the structure of an image processing apparatus according to an embodiment of the present invention, as shown in fig. 4, the apparatus including: a first obtaining module 42, configured to obtain a set of image data of a frame of image collected by a wide dynamic sensor, where the wide dynamic sensor is disposed on an image collecting device, and the set of image data includes long frame data and short frame data; a first upload module 44 for uploading the long frame data to a first image processor to identify a person object in the one frame image by the first image processor; a second upload module 46 for uploading the short frame data to a second image processor to identify the vehicle object in the one frame image by the second image processor; a second obtaining module 48, configured to obtain the human object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor.
As an alternative embodiment, uploading the long frame data to a first image processor to identify a human object in the frame of image by the first image processor, includes: uploading the long frame data to a first image processor; the first image processor adjusts the frame of image according to the exposure duration of the character object in the frame of image and a first adjustment parameter to obtain a first image; the first image processor identifies the person objects in the first image and the number of the person objects, wherein the person object identification result comprises the person objects in the first image and the number of the person objects.
As an alternative embodiment, uploading the short frame data to a second image processor to identify the vehicle object in the frame of image by the second image processor, includes: uploading the short frame data to a second image processor; the second image processor adjusts the frame of image according to a second adjustment parameter and the exposure duration of the vehicle object in the frame of image to obtain a second image; the second image processor identifies the vehicle object in the second image and the number of the vehicle objects, wherein the vehicle object identification result comprises the vehicle object in the first image and the number of the vehicle objects.
As an optional embodiment, the method further comprises: and uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the character object in the frame image and the exposure duration of the vehicle object in the frame image to obtain a third image.
As an optional embodiment, the uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the person object in the frame image and the exposure duration of the vehicle object in the frame image, to obtain a third image, includes: the third image processor acquires a first adjusting parameter when the first image processor adjusts the frame of image and a second adjusting parameter when the second image processor adjusts the frame of image; the third image processor determines the third adjustment parameter according to the first adjustment parameter and the second adjustment parameter, wherein the third adjustment parameter is between the first adjustment parameter and the second adjustment parameter; and the third image processor adjusts the frame of image according to the third adjustment parameter to obtain the third image.
As an optional embodiment, the method further comprises: in a case where it is determined that the number of the human objects in the one frame image is larger than a first threshold value and the number of the vehicle objects is smaller than a second threshold value, displaying a human object recognition result output by the first image processor; in a case where it is determined that the number of the human objects in the one frame image is smaller than a first threshold and the number of the vehicle objects is larger than a second threshold, displaying a vehicle object recognition result output by the second image processor; and displaying a third image output by a third image processor in the case where it is determined that the number of the human objects in the one frame image is greater than a first threshold and the number of the vehicle objects is greater than a second threshold.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on an image acquisition device, and the group of image data comprises long frame data and short frame data;
s2, uploading the long frame data to a first image processor to identify a character object in the frame of image by the first image processor;
s3, uploading the short frame data to a second image processor so as to identify the vehicle object in the frame image through the second image processor;
s4, acquiring the result of recognition of the character object output by the first image processor and the result of recognition of the vehicle object output by the second image processor.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on an image acquisition device, and the group of image data comprises long frame data and short frame data;
s2, uploading the long frame data to a first image processor to identify a character object in the frame of image by the first image processor;
s3, uploading the short frame data to a second image processor so as to identify the vehicle object in the frame image through the second image processor;
s4, acquiring the result of recognition of the character object output by the first image processor and the result of recognition of the vehicle object output by the second image processor.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An image processing method, comprising:
acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, wherein the wide dynamic sensor is arranged on an image acquisition device, and the group of image data comprises long frame data and short frame data;
uploading the long frame data to a first image processor to identify a character object in the frame of image through the first image processor;
uploading the short frame data to a second image processor to identify a vehicle object in the one frame image by the second image processor;
and acquiring a character object recognition result output by the first image processor and a vehicle object recognition result output by the second image processor.
2. The method of claim 1, wherein uploading the long frame data to a first image processor for identifying human objects in the frame of images by the first image processor comprises:
uploading the long frame data to a first image processor;
the first image processor adjusts the frame of image according to the exposure duration of the character object in the frame of image and a first adjustment parameter to obtain a first image;
the first image processor identifies the person objects in the first image and the number of the person objects, wherein the person object identification result comprises the person objects in the first image and the number of the person objects.
3. The method of claim 1, wherein uploading the short frame data to a second image processor to identify a vehicle object in the one frame image by the second image processor comprises:
uploading the short frame data to a second image processor;
the second image processor adjusts the frame of image according to a second adjustment parameter and the exposure duration of the vehicle object in the frame of image to obtain a second image;
the second image processor identifies the vehicle object in the second image and the number of the vehicle objects, wherein the vehicle object identification result comprises the vehicle object in the first image and the number of the vehicle objects.
4. The method of claim 1, further comprising:
and uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the frame image according to a third adjustment parameter according to the exposure duration of the character object in the frame image and the exposure duration of the vehicle object in the frame image to obtain a third image.
5. The method of claim 4, wherein uploading the long frame data and the short frame data to a third image processor, so that the third image processor adjusts the one frame image according to a third adjustment parameter according to the exposure duration of the human object in the one frame image and the exposure duration of the vehicle object in the one frame image, and obtains a third image, comprises:
the third image processor acquires a first adjusting parameter when the first image processor adjusts the frame of image and a second adjusting parameter when the second image processor adjusts the frame of image;
the third image processor determines the third adjustment parameter according to the first adjustment parameter and the second adjustment parameter, wherein the third adjustment parameter is between the first adjustment parameter and the second adjustment parameter;
and the third image processor adjusts the frame of image according to the third adjustment parameter to obtain the third image.
6. The method according to claim 4 or 5, characterized in that the method further comprises:
in a case where it is determined that the number of the human objects in the one frame image is larger than a first threshold value and the number of the vehicle objects is smaller than a second threshold value, displaying a human object recognition result output by the first image processor;
in a case where it is determined that the number of the human objects in the one frame image is smaller than a first threshold and the number of the vehicle objects is larger than a second threshold, displaying a vehicle object recognition result output by the second image processor;
and displaying a third image output by a third image processor in the case where it is determined that the number of the human objects in the one frame image is greater than a first threshold and the number of the vehicle objects is greater than a second threshold.
7. An image processing apparatus characterized by comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a group of image data of one frame of image acquired by a wide dynamic sensor, the wide dynamic sensor is arranged on image acquisition equipment, and the group of image data comprises long frame data and short frame data;
a first uploading module, configured to upload the long frame data to a first image processor, so as to identify a person object in the frame of image through the first image processor;
a second uploading module, configured to upload the short frame data to a second image processor, so as to identify, by the second image processor, a vehicle object in the frame of image;
and the second acquisition module is used for acquiring the character object recognition result output by the first image processor and the vehicle object recognition result output by the second image processor.
8. An image processing system, comprising:
the image processing device comprises a first image processor, a second image processor and a processing unit, wherein the first image processor is used for acquiring long frame data of one frame of image acquired by a wide dynamic sensor and identifying a character object in the one frame of image through the long frame data;
the second image processor is used for acquiring short frame data of one frame of image acquired by the wide dynamic sensor, and identifying the vehicle object in the one frame of image through the short frame data;
and the third image processor is used for determining a third adjustment parameter according to the first adjustment parameter when the first image processor adjusts the frame of image and the second adjustment parameter when the second image processor adjusts the frame of image, and adjusting the frame of image according to the third adjustment parameter to obtain a third image.
9. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 6 when executed.
10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 6.
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