Image processing method, image recognition method, control apparatus, readable medium, and device

Abstract

The present application relates to the technical field of images, and particularly provides an image processing method, an image recognition method, a control apparatus, a readable medium, and a device, aiming to solve the problem of accurate AON recognition on the premise of low power consumption. For this purpose, in the present application, an image sensor of a terminal device acquires a current image; a current ambient light brightness is acquired on the basis of an ambient light sensor; a current ambient scenario is acquired on the basis of the ambient light brightness; and image correction is performed on the image on the basis of the ambient scenario, so as to obtain a corrected image. By means of the configuration mode above, in the present application, different ambient scenarios can be distinguished on the basis of different ambient light brightnesses, so that distinguished image correction is performed on the image on the basis of the different ambient scenarios; and the image quality of the corrected image in different ambient scenarios can be effectively improved without the need for applying rich ISP functions, and a recognition effect of an AON function can be effectively ensured while the power consumption of the terminal device is reduced.

Description

Image processing, image recognition method, control device, readable medium and device This application claims priority to Chinese patent application CN 202311757153.6, filed on December 19, 2023, with the invention name “Image processing, image recognition method, control device, readable medium and equipment”. The entire content of the above Chinese patent application is incorporated into this application by reference. Technical Field

[0001] The present application relates to the field of image technology, and specifically provides an image processing and image recognition method, a control device, a readable medium and a device. Background Art

[0002] Currently, there are two main solutions for implementing the AON function on mobile phones, that is, face recognition and face gaze using the always-on camera. The first solution is for the main processor to directly call the front camera to shoot, and then recognize the face or gaze in the security processor or main processor; the second solution is to call the front camera in low-power mode in the low-power processor to capture the image, and recognize the face or gaze in the low-power processor. The first solution can process the image by using the rich ISP (Image Signal Processing) function, so that the output image remains clear under different ambient light brightness, but this solution requires AP wake-up and consumes a lot of power; the second solution has lower power consumption and only simple gamma processing. It cannot process images according to different ambient light conditions. The output image quality is low in dark scenes, strong backlighting, and other scenes, which affects face recognition and gaze recognition.

[0003] Accordingly, a new image processing solution is needed in this field to solve the above problems. Summary of the Invention

[0004] In order to overcome the above-mentioned defects, the present application is proposed to provide a solution or at least partially solve the problem of achieving accurate AON identification under the premise of low power consumption.

[0005] In a first aspect, the present application provides an image processing method, which is applied to a terminal device, wherein the terminal device is provided with an image sensor and an ambient light sensor; the method comprises:

[0006] Acquire a current image through the image sensor;

[0007] Acquiring the ambient light brightness corresponding to the image through the ambient light sensor;

[0008] Acquiring an environmental scene corresponding to the image according to the ambient light brightness;

[0009] Based on the environmental scene, image correction is performed on the image to obtain a corrected image.

[0010] In one technical solution of the above-mentioned image processing method, performing image correction on the image based on the environmental scene to obtain the corrected image includes:

[0011] According to the environmental scene, obtaining a gamma coefficient corresponding to the environmental scene;

[0012] Perform image correction on the image according to the gamma coefficient to obtain the corrected image.

[0013] In one technical solution of the above image processing method, the method further includes obtaining a gamma coefficient corresponding to the environmental scene according to the following steps:

[0014] Acquire an image set for obtaining the gamma coefficient, and obtain the ambient light brightness corresponding to each image in the image set;

[0015] Acquiring an environmental scene corresponding to the image according to the ambient light brightness;

[0016] For each environmental scene image, multiple adjustment gamma coefficients are obtained according to a preset gamma coefficient initial value and a preset step;

[0017] Correcting the image according to each of the adjusted gamma coefficients to obtain a corrected image corresponding to each of the adjusted gamma coefficients;

[0018] Performing image recognition on the corrected image to obtain an image recognition result;

[0019] According to the image recognition result, a gamma coefficient corresponding to the environmental scene is obtained.

[0020] In one technical solution of the above-mentioned image processing method, obtaining the gamma coefficient corresponding to the environmental scene according to the image recognition result includes:

[0021] For each of the adjusted gamma coefficients, obtaining a mean confidence value of the image recognition results of the image in the same environmental scene;

[0022] The adjusted gamma coefficient with the largest confidence mean is selected as the gamma coefficient corresponding to the environmental scene.

[0023] In one technical solution of the above image processing method, the ambient light brightness includes front ambient light brightness and rear ambient light brightness;

[0024] The acquiring, according to the ambient light brightness, an environmental scene corresponding to the image, includes:

[0025] The environmental scene is acquired according to the front ambient light brightness and the rear ambient light brightness.

[0026] In one technical solution of the above-mentioned image processing method, the image sensor is a front image sensor, and the environmental scene includes a dark scene, a front-lit scene, a backlit scene, and a normal-light scene;

[0027] The acquiring the environmental scene according to the front ambient light brightness and the rear ambient light brightness includes:

[0028] When the front ambient light brightness and the rear ambient light brightness are both less than a first preset brightness, determining that the ambient scene is the dark scene;

[0029] When the front ambient light brightness and the rear ambient light brightness are both greater than a second preset brightness, and a difference obtained by subtracting the rear ambient light brightness from the front ambient light brightness is greater than a third preset brightness, determining that the ambient scene is the surface light scene;

[0030] When the front ambient light brightness and the rear ambient light brightness are both greater than a second preset brightness, and a difference obtained by subtracting the front ambient light brightness from the rear ambient light brightness is greater than a third preset brightness, determining that the ambient scene is the backlit scene;

[0031] When the front ambient light brightness and the rear ambient light brightness do not meet the above conditions, determining that the ambient scene is the normal light scene;

[0032] The first preset brightness is smaller than the third preset brightness and smaller than the second preset brightness, and the first preset brightness is greater than zero.

[0033] In one technical solution of the above image processing method, the ambient light sensor includes a front ambient light sensor and a rear ambient light sensor; the ambient light brightness includes a front ambient light brightness and a rear ambient light brightness;

[0034] The step of obtaining the ambient light brightness corresponding to the image by using the ambient light sensor includes:

[0035] Acquiring the front ambient light brightness through the front ambient light sensor;

[0036] The rear ambient light brightness is obtained through the rear ambient light sensor.

[0037] In one technical solution of the above-mentioned image processing method, acquiring the current image through the image sensor includes:

[0038] Acquire a low-resolution image using the image sensor as the current image;

[0039] The low-resolution image is an image with a resolution smaller than the VGA resolution.

[0040] In a technical solution of the above-mentioned image processing method, the current image is an image with a QVGA resolution or a QQVGA resolution.

[0041] In a second aspect, the present application provides an image recognition method, the method comprising:

[0042] Acquire an image to be recognized, wherein the image is a corrected image obtained by the image processing method described in any one of the above image processing methods;

[0043] Image recognition is performed based on the image to be recognized to obtain an image recognition result.

[0044] In one technical solution of the above-mentioned image recognition method, performing image recognition based on the image to be recognized to obtain an image recognition result includes:

[0045] Perform face recognition based on the image to be recognized to obtain a face recognition result.

[0046] In one technical solution of the above-mentioned image recognition method, performing image recognition based on the image to be recognized to obtain an image recognition result includes:

[0047] Perform gaze recognition according to the image to be recognized to obtain a gaze recognition result.

[0048] In a third aspect, a control device is provided, which includes at least one processor and at least one storage device, wherein the storage device is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute the image processing method described in any one of the technical solutions of the above-mentioned image processing method or the image recognition method described in any one of the technical solutions of the above-mentioned image recognition method.

[0049] In one technical solution of the above-mentioned image recognition method, the processor is a low-power processor.

[0050] In a fourth aspect, a computer-readable storage medium is provided, which stores a plurality of program codes, wherein the program codes are suitable for being loaded and run by a processor to execute the image processing method described in any one of the technical solutions of the above-mentioned image processing method or the image recognition method described in any one of the technical solutions of the above-mentioned image recognition method.

[0051] In a fifth aspect, a terminal device is provided, wherein an image sensor and an ambient light sensor are provided on the terminal device, and the terminal device includes a control device according to any one of the above-mentioned technical solutions of the control device.

[0052] The above one or more technical solutions of this application have at least one or more of the following beneficial effects:

[0053] In implementing the technical solution of the present application, the image sensor of the terminal device of the present application obtains the current image, obtains the current ambient light brightness according to the ambient light sensor, obtains the current environmental scene according to the ambient light brightness, and performs image correction on the image according to the environmental scene, thereby obtaining a corrected image. Through the above configuration, the present application can distinguish different environmental scenes according to different ambient light brightness, thereby performing differential image correction on the image according to different environmental scenes. Without applying rich ISP functions, the image quality of the corrected image in different environmental scenes can be effectively improved. While reducing the power consumption of the terminal device, it can effectively ensure the recognition effect of the AON function.

[0054] Furthermore, the present application obtains the front ambient light brightness and rear ambient light brightness of the terminal device respectively, and obtains the environmental scene according to the front ambient light brightness and rear ambient light brightness, which can accurately distinguish different environmental scenes, thereby performing image correction according to different environmental scenes to further improve image quality.

[0055] Furthermore, the present application sets a corresponding gamma coefficient for each environmental scene. Calling the corresponding gamma coefficient based on different environmental scenes to correct the image can make the image clearer, thereby further improving the image quality in different environmental scenes and effectively ensuring the recognition effect of the AON function. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The disclosure of this application will become more easily understood with reference to the accompanying drawings. Those skilled in the art will readily appreciate that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Among them:

[0057] FIG1 is a schematic flow chart of main steps of an image processing method according to an embodiment of the present application;

[0058] FIG2 is a schematic flow chart of main steps of an image processing method according to an embodiment of the present application;

[0059] FIG3 is a flow chart showing the main steps of an image recognition method according to an embodiment of the present application;

[0060] FIG4 is a schematic diagram of a main structural block diagram of an image processing system according to an embodiment of the present application;

[0061] FIG5 is a schematic diagram of a main structural block diagram of an image recognition system according to an embodiment of the present application. DETAILED DESCRIPTION

[0062] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the scope of protection of the present application.

[0063] In the description of this application, "module" and "processor" may include hardware, software, or a combination of both. A module may include hardware circuitry, various suitable sensors, communication ports, and memory. It may also include software components, such as program code, or a combination of software and hardware. A processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. A processor has data and / or signal processing capabilities. A processor may be implemented in software, hardware, or a combination of both. Non-transitory computer-readable storage media include any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" refers to all possible combinations of A and B, such as only A, only B, or both A and B. The terms "at least one of A or B" or "at least one of A and B" have similar meanings to "A and / or B" and may include only A, only B, or both A and B. The singular forms "a" and "the" may also include the plural forms.

[0064] Referring to Figure 1 , Figure 1 is a schematic flow diagram illustrating the main steps of an image processing method according to an embodiment of the present application. As shown in Figure 1 , the image processing method in this embodiment of the present application is applied to a terminal device, which may be equipped with an image sensor and an ambient light sensor. The image processing method primarily includes the following steps S101 through S104 .

[0065] Step S101: Acquire the current image through the image sensor.

[0066] In this embodiment, the current image may be captured by an image sensor.

[0067] In one embodiment, the terminal device may be a smart phone, a tablet computer, an intelligent controller, or the like.

[0068] In one embodiment, the image sensor may be a camera provided on the terminal device. For images used to implement the AON function, the image sensor may be a front-facing camera for capturing facial images.

[0069] In one embodiment, an image sensor can capture a low-resolution image as the current image. A low-resolution image is image data with a resolution lower than the VGA resolution. This means capturing a low-resolution image supported by the image sensor, which effectively reduces power consumption. The VGA (Video Graphics Array) resolution is 640 pixels x 480 pixels. Therefore, a low-resolution image is one with a resolution lower than 640 pixels x 480 pixels.

[0070] In one embodiment, the current image may be an image having a QVGA (Quarter Video Graphics Array) resolution or a QQVGA (Quarter Quarter Video Graphics Array) resolution, wherein the QVGA resolution is 320 pixels × 240 pixels and the QQVGA resolution is 120 pixels × 160 pixels. It should be noted that the above resolutions are merely exemplary and the present application is not limited to the above resolutions.

[0071] Step S102: Obtaining the ambient light brightness corresponding to the image through the ambient light sensor.

[0072] In this embodiment, the current ambient light brightness may be acquired through an ambient light sensor.

[0073] In one embodiment, the ambient light sensor may include a front ambient light sensor and a rear ambient light sensor, that is, ambient light sensors are provided on both the user-facing side and the non-user-facing side of the terminal device.

[0074] Step S103: Acquire the environment scene corresponding to the image according to the ambient light brightness.

[0075] In this embodiment, the current environmental scene may be determined according to the collected ambient light brightness.

[0076] In one embodiment, the environmental scenes may include a front-lit scene, a backlit scene, a dark scene, and a normal-light scene. The current environmental scene may be distinguished based on different values ​​of the ambient light brightness.

[0077] Step S104: performing image correction on the image based on the environmental scene to obtain a corrected image.

[0078] In this embodiment, the image may be corrected based on the environmental scene to obtain a corrected image.

[0079] In one embodiment, bright field uniformity correction may be performed on the image according to the environmental scene to obtain a corrected image.

[0080] In one embodiment, LUT (Look-Up Table) correction can be performed on the image according to the environmental scene to obtain a corrected image.

[0081] Based on the above steps S101-S104, the image sensor of the terminal device of the embodiment of the present application obtains the current image, obtains the current ambient light brightness according to the ambient light sensor, obtains the current environmental scene according to the ambient light brightness, and performs image correction on the image according to the environmental scene, thereby obtaining a corrected image. Through the above configuration, the embodiment of the present application can distinguish different environmental scenes according to different ambient light brightness, thereby performing differential image correction on the image according to different environmental scenes, and can effectively improve the image quality of the corrected image in different environmental scenes without applying rich ISP functions, while reducing the power consumption of the terminal device, and can effectively ensure the recognition effect of the AON function.

[0082] Step S102, step S103 and step S104 are further described below.

[0083] In one implementation of the embodiment of the present application, the ambient light brightness includes the front ambient light brightness and the rear ambient light brightness, and step S102 may further include the following steps S1021 and S1022:

[0084] Step S1021: Obtain the front ambient light brightness through the front ambient light sensor.

[0085] Step S1022: Obtain the rear ambient light brightness through the rear ambient light sensor.

[0086] In this embodiment, the front ambient light brightness can be obtained by the front ambient light sensor, and the rear ambient light brightness can be obtained by the rear ambient light sensor. Acquiring the front ambient light brightness and the rear ambient light brightness separately can further obtain a more accurate environmental scene.

[0087] In one implementation of the embodiment of the present application, step S103 is further configured as follows:

[0088] Get the ambient scene based on the front ambient light brightness and the rear ambient light brightness.

[0089] In this embodiment, the environmental scene may include a dark scene, a front-light scene, a backlight scene, and a normal-light scene. Step S103 may further include the following steps S1031 to S1034:

[0090] Step S1031: when the brightness of the front ambient light and the brightness of the rear ambient light are both less than a first preset brightness, determining that the ambient scene is a dark scene;

[0091] Step S1032: When both the front ambient light brightness and the rear ambient light brightness are greater than the second preset brightness, and the difference between the front ambient light brightness and the rear ambient light brightness is greater than the third preset brightness, the ambient scene is determined to be a surface light scene.

[0092] Step S1033: When both the front ambient light brightness and the rear ambient light brightness are greater than the second preset brightness, and the difference between the rear ambient light brightness and the front ambient light brightness is greater than the third preset brightness, it is determined that the ambient scene is a backlit scene.

[0093] Step S1034: When both the front ambient light brightness and the rear ambient light brightness do not meet the above conditions, the ambient scene is determined to be a normal light scene; wherein the first preset brightness is less than the third preset brightness and less than the second preset brightness, and the first preset brightness is greater than zero.

[0094] In this embodiment, it is assumed that the front ambient light brightness is Lfront and the rear ambient light brightness is Lrear.

[0095] When Lfront<the first preset brightness and Lrear<the first preset brightness, it is a dark scene;

[0096] When Lfront>the second preset brightness, Lrear>the second preset brightness, and Lfront-Lrear>the third preset brightness, it is a front light scene;

[0097] When Lfront> the second preset brightness, and Lrear> the second preset brightness, and Lrear-Lfront> the third preset brightness, it is a backlight scene.

[0098] The rest are normal light scenes.

[0099] A front-lit scene is one where the direction of light projection is consistent with the image sensor's shooting direction. A backlit scene is one where light is projected from the back or diagonally behind the subject.

[0100] In one embodiment, the first preset brightness may be 5 lux, the second preset brightness may be 500 lux, and the third preset brightness may be 200 lux.

[0101] It should be noted that the values ​​of the first preset brightness, the second preset brightness and the third preset brightness are only exemplary. Those skilled in the art can set the values ​​of the first preset brightness, the second preset brightness and the third preset brightness according to the needs of actual application.

[0102] In one implementation of the embodiment of the present application, step S104 may further include the following steps S1041 and S1042:

[0103] Step S1041: Obtain the gamma coefficient corresponding to the environmental scene according to the environmental scene.

[0104] The gamma coefficient is a coefficient used to perform gamma correction on an image. Gamma correction is a nonlinear transformation used to correct image brightness. The gamma coefficient determines the grayscale mapping relationship between the input image and the output image during the gamma correction process.

[0105] In this embodiment, the gamma coefficient corresponding to the environmental scene can be obtained according to the following steps S201 to S206.

[0106] Step S201: Acquire an image set for obtaining a gamma coefficient, and obtain the ambient light brightness corresponding to each image in the image set.

[0107] In this embodiment, a set of images for obtaining a gamma coefficient may be collected, and the ambient light brightness corresponding to each image may be obtained.

[0108] Step S202: Acquire the environment scene corresponding to the image according to the ambient light brightness.

[0109] In this embodiment, the method described in steps S1031 to S1034 may be used to obtain the environmental scene corresponding to the image according to the ambient light brightness.

[0110] Step S203: For each image of the environment scene, obtain multiple adjustment gamma coefficients according to the preset gamma coefficient initial value and preset step

[0111] In this embodiment, for each image of an environmental scene, an initial value of a gamma coefficient and a preset step may be set to obtain a plurality of adjusted gamma coefficients.

[0112] In one embodiment, the initial value of the gamma coefficient may be 0.1, and the preset step may be 0.1. That is, 0.1 may be used as the initial value, and multiple adjusted gamma coefficients may be obtained with a step of 0.1, and the maximum value of the gamma coefficient is 1.

[0113] Step S204: Correct the image according to each adjusted gamma coefficient to obtain a corrected image corresponding to each adjusted gamma coefficient.

[0114] In this embodiment, gamma correction may be performed on the image according to each adjusted gamma coefficient to obtain a corrected image corresponding to each adjusted gamma coefficient.

[0115] Step S205: performing image recognition on the corrected image to obtain an image recognition result.

[0116] In this embodiment, the corrected image is subjected to image recognition to obtain an image recognition result.

[0117] In one embodiment, the image recognition may be gaze recognition, that is, applying a gaze recognition algorithm to perform image recognition on the corrected image.

[0118] In one embodiment, the image recognition may be face recognition, that is, applying a face recognition algorithm to perform image recognition on the corrected image.

[0119] Step S206: Obtain the gamma coefficient corresponding to the environmental scene according to the image recognition result.

[0120] In this embodiment, step S206 may further include the following steps S2061 and S2062:

[0121] Step S2061: for each adjusted gamma coefficient, obtain the confidence mean of the image recognition results of the image in the same environmental scene.

[0122] Step S2062: Select the adjusted gamma coefficient with the largest confidence mean as the gamma coefficient corresponding to the environmental scene.

[0123] In this embodiment, for each environmental scene, a corrected image that has been gamma-corrected using different adjusted gamma coefficients may be used for image recognition to obtain a confidence level for the image recognition result. The confidence levels of the image recognition results corresponding to the adjusted gamma coefficients are averaged to obtain a mean confidence level. The adjusted gamma coefficient with the largest mean confidence level is selected as the gamma coefficient corresponding to the environmental scene.

[0124] Step S1042: performing image correction on the image according to the gamma coefficient to obtain a corrected image.

[0125] In this embodiment, gamma correction may be performed on the image according to the gamma coefficient to obtain a corrected image.

[0126] In one embodiment, reference may be made to FIG2 , which is a flow chart illustrating the main steps of an image processing method according to an embodiment of the present application. As shown in FIG2 , an image may be outputted by a front camera in low power mode, an image M may be acquired by a low power camera (AON), front and rear ambient light brightness (front ambient light brightness and rear ambient light brightness) F_LUX and R_LUX may be acquired based on the front ambient light sensor F_ALS and the rear ambient light sensor R_AL, dark, backlight, face light, and normal light scenes may be distinguished based on the front and rear ambient light brightness, a corresponding gamma curve may be selected for image processing according to different scenes, the processed image may be recognized by an algorithm, face and gaze recognition results may be output, and transmitted to the main processor.

[0127] Furthermore, the present application also provides an image recognition method.

[0128] 3, which is a flow chart of the main steps of an image recognition method according to an embodiment of the present application. As shown in FIG3, the image recognition method in the embodiment of the present application mainly includes the following steps S301 to S302.

[0129] Step S301: Acquire an image to be recognized, wherein the image is a corrected image obtained according to the image processing method described in the above-mentioned embodiment of the image processing method.

[0130] Step S302: performing image recognition based on the image to be recognized to obtain an image recognition result.

[0131] In this embodiment, since the image acquired by the image processing method embodiment is corrected based on the environmental scene, it is possible to ensure image quality without the need for rich ISP functions, and then perform image recognition based on the acquired image to ensure the accuracy of the image recognition result.

[0132] In one embodiment, step S302 may include the following steps S3021:

[0133] Step S3021: Perform face recognition based on the image to be recognized and obtain a face recognition result.

[0134] In this embodiment, face recognition can be performed based on the image to be recognized to obtain a face recognition result.

[0135] In one embodiment, step S302 may include the following steps S3022:

[0136] Step S3022: performing gaze recognition according to the image to be recognized, and obtaining a gaze recognition result.

[0137] In this embodiment, gaze recognition may be performed based on the image to be recognized to obtain a gaze recognition result.

[0138] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of the present application, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present application.

[0139] Furthermore, the present application also provides an image processing system.

[0140] Refer to Figure 4, which is a main structural block diagram of an image processing system according to an embodiment of the present application. As shown in Figure 4, the image processing system in the embodiment of the present application is applied to a terminal device, and an image sensor and an ambient light sensor are provided on the terminal device. The image processing system mainly includes an image acquisition module, an ambient light brightness acquisition module, an ambient scene acquisition module and an image correction module. In this embodiment, the image acquisition module can be configured to acquire the current image through the image sensor. The ambient light brightness acquisition module can be configured to acquire the ambient light brightness corresponding to the image through the ambient light sensor. The ambient scene acquisition module can be configured to acquire the ambient scene corresponding to the image based on the ambient light brightness. The image correction module can be configured to perform image correction on the image based on the ambient scene to acquire the corrected image.

[0141] The above-mentioned image processing system is used to execute the embodiment of the image processing method shown in Figure 1. The technical principles, technical problems solved and technical effects produced by the two are similar. Technical personnel in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the image processing system can refer to the contents described in the embodiment of the image processing method, and will not be repeated here.

[0142] Furthermore, the present application also provides an image recognition system.

[0143] Referring to Figure 5, Figure 5 is a block diagram of the main structure of an image recognition system according to one embodiment of the present application. As shown in Figure 5, the image recognition system in this embodiment of the present application mainly includes an image acquisition module to be recognized and an image recognition module. In this embodiment, the image acquisition module can be configured to acquire an image to be recognized, where the image is a corrected image obtained according to the image processing method described in the above-mentioned image processing method embodiment. The image recognition module can be configured to perform image recognition based on the image to be recognized and obtain an image recognition result.

[0144] The above-mentioned image recognition system is used to execute the embodiment of the image recognition method shown in Figure 3. The technical principles, technical problems solved and technical effects produced by the two are similar. Technical personnel in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the image recognition system can refer to the contents described in the embodiment of the image recognition method, and will not be repeated here.

[0145] It will be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment of the present application can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0146] Furthermore, the present application also provides a control device. In a control device embodiment according to the present application, the control device includes a processor and a storage device. The storage device can be configured to store a program for executing the image processing method of the above-mentioned method embodiment, and the processor can be configured to execute the program in the storage device, which includes but is not limited to a program for executing the image processing method of the above-mentioned method embodiment. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The control device can be a control device device formed by various electronic devices.

[0147] In the embodiment of the present application, the control device may be a control device device formed by various electronic devices. In some possible implementations, the control device may include multiple storage devices and multiple processors. The program for executing the image processing method of the above-mentioned method embodiment can be divided into multiple subroutines, and each subroutine can be loaded and run by the processor to execute different steps of the image processing method of the above-mentioned method embodiment. Specifically, each subroutine can be stored in different storage devices respectively, and each processor can be configured to execute the programs in one or more storage devices to jointly implement the image processing method of the above-mentioned method embodiment, that is, each processor executes different steps of the image processing method of the above-mentioned method embodiment respectively to jointly implement the image processing method of the above-mentioned method embodiment.

[0148] The aforementioned multiple processors may be processors deployed on the same device. For example, the aforementioned control device may be a high-performance device composed of multiple processors, and the aforementioned multiple processors may be processors configured on the high-performance device. Furthermore, the aforementioned multiple processors may also be processors deployed on different devices. For example, the aforementioned control device may be a server cluster, and the aforementioned multiple processors may be processors on different servers in the server cluster.

[0149] In one embodiment, the processor of the control device is a low-power processor.

[0150] Furthermore, the present application also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present application, the computer-readable storage medium can be configured to store a program for executing the image processing method of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned image processing method. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present application is a non-temporary computer-readable storage medium.

[0151] Furthermore, the present application also provides a control device. In a control device embodiment according to the present application, the control device includes a processor and a storage device. The storage device can be configured to store a program for executing the image recognition method of the above-mentioned method embodiment, and the processor can be configured to execute the program in the storage device, which includes but is not limited to a program for executing the image recognition method of the above-mentioned method embodiment. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The control device can be a control device device formed by various electronic devices.

[0152] In the embodiment of the present application, the control device may be a control device device formed by various electronic devices. In some possible implementations, the control device may include multiple storage devices and multiple processors. The program for executing the image recognition method of the above-mentioned method embodiment can be divided into multiple subroutines, and each subroutine can be loaded and run by the processor to execute different steps of the image recognition method of the above-mentioned method embodiment. Specifically, each subroutine can be stored in different storage devices respectively, and each processor can be configured to execute the program in one or more storage devices to jointly implement the image recognition method of the above-mentioned method embodiment, that is, each processor executes different steps of the image recognition method of the above-mentioned method embodiment respectively to jointly implement the image recognition method of the above-mentioned method embodiment.

[0153] The aforementioned multiple processors may be processors deployed on the same device. For example, the aforementioned control device may be a high-performance device composed of multiple processors, and the aforementioned multiple processors may be processors configured on the high-performance device. Furthermore, the aforementioned multiple processors may also be processors deployed on different devices. For example, the aforementioned control device may be a server cluster, and the aforementioned multiple processors may be processors on different servers in the server cluster.

[0154] Furthermore, the present application also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present application, the computer-readable storage medium can be configured to store a program for executing the image recognition method of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned image recognition method. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present application is a non-temporary computer-readable storage medium.

[0155] Furthermore, the present application also provides a terminal device. In one embodiment of the terminal device according to the present application, the terminal device is provided with an image sensor and an ambient light sensor, and the terminal device includes the control device in the control device embodiment.

[0156] Furthermore, it should be understood that since the configuration of each module is merely for the purpose of illustrating the functional units of the apparatus of the present application, the physical devices corresponding to these modules may be the processor itself, or a portion of the software in the processor, a portion of the hardware, or a combination of software and hardware. Therefore, the number of modules in the figure is merely illustrative.

[0157] Those skilled in the art will appreciate that the various modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principles of this application. Therefore, the technical solutions after splitting or merging will fall within the scope of protection of this application.

[0158] The relevant user personal information that may be involved in the various embodiments of this application is strictly in accordance with the requirements of laws and regulations, following the principles of legality, legitimacy and necessity, and based on the reasonable purposes of business scenarios, to process the personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as the personal information obtained with the user's authorization.

[0159] The user personal information processed in this application will vary depending on the specific product / service scenario and will be based on the specific scenario in which the user uses the product / service. This may involve the user's account information, device information, driving information, vehicle information, or other related information. The applicant will treat the user's personal information and its processing with a high degree of diligence.

[0160] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0161] Thus far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present application.

Claims

1. An image processing method, characterized in that: The method is applied to a terminal device, and the terminal device is provided with an image sensor and an ambient light sensor; the method comprises: Acquire a current image through the image sensor; Acquiring the ambient light brightness corresponding to the image through the ambient light sensor; Acquire the environment scene corresponding to the image according to the ambient light brightness; Based on the environmental scene, image correction is performed on the image to obtain a corrected image.

2. The image processing method according to claim 1, characterized in that: The step of performing image correction on the image based on the environmental scene to obtain a corrected image includes: According to the environmental scene, obtaining a gamma coefficient corresponding to the environmental scene; Image correction is performed on the image according to the gamma coefficient to obtain the corrected image.

3. The image processing method according to claim 2, characterized in that: The method further includes obtaining a gamma coefficient corresponding to the environmental scene according to the following steps: Acquire an image set for obtaining the gamma coefficient, and obtain the ambient light brightness corresponding to each image in the image set; Acquire the environment scene corresponding to the image according to the ambient light brightness; For each image of the environment scene, multiple adjustment gamma coefficients are obtained according to a preset gamma coefficient initial value and a preset step; Correcting the image according to each of the adjusted gamma coefficients to obtain a corrected image corresponding to each of the adjusted gamma coefficients; Performing image recognition on the corrected image to obtain an image recognition result; According to the image recognition result, a gamma coefficient corresponding to the environmental scene is obtained.

4. The image processing method according to claim 3, characterized in that: The obtaining, according to the image recognition result, a gamma coefficient corresponding to the environmental scene includes: For each of the adjusted gamma coefficients, obtaining a mean confidence value of the image recognition results of the image in the same environment scene; The adjusted gamma coefficient with the largest confidence mean is selected as the gamma coefficient corresponding to the environmental scene.

5. The image processing method according to any one of claims 1 to 4, characterized in that: The ambient light brightness includes the front ambient light brightness and the rear ambient light brightness; The acquiring, according to the ambient light brightness, an environmental scene corresponding to the image comprises: The environmental scene is acquired according to the front ambient light brightness and the rear ambient light brightness.

6. The image processing method according to claim 5, characterized in that: The image sensor is a front image sensor, and the environmental scenes include dark scenes, front-lit scenes, backlit scenes, and normal-light scenes; The acquiring the environmental scene according to the front ambient light brightness and the rear ambient light brightness includes: When the front ambient light brightness and the rear ambient light brightness are both less than a first preset brightness, determining that the ambient scene is the dark scene; When the front ambient light brightness and the rear ambient light brightness are both greater than the second preset brightness, and the difference obtained by subtracting the rear ambient light brightness from the front ambient light brightness is greater than the third preset brightness, determining that the ambient scene is the surface light scene; When the front ambient light brightness and the rear ambient light brightness are both greater than the second preset brightness, and the difference between the rear ambient light brightness and the front ambient light brightness is greater than the third preset brightness, determining that the ambient scene is the backlit scene; When the front ambient light brightness and the rear ambient light brightness do not meet the above conditions, determining that the ambient scene is the normal light scene; The first preset brightness is smaller than the third preset brightness and smaller than the second preset brightness, and the first preset brightness is greater than zero.

7. The image processing method according to claim 1, characterized in that: The ambient light sensor includes a front ambient light sensor and a rear ambient light sensor; the ambient light brightness includes a front ambient light brightness and a rear ambient light brightness; The step of obtaining the ambient light brightness corresponding to the image through the ambient light sensor includes: Acquiring the front ambient light brightness through the front ambient light sensor; The rear ambient light brightness is obtained through the rear ambient light sensor.

8. The image processing method according to any one of claims 1 to 7, characterized in that: The step of acquiring the current image through the image sensor includes: By means of the image sensor, a low-resolution image is acquired as the current image; The low-resolution image is an image with a resolution smaller than the VGA specification resolution.

9. The image processing method according to claim 8, characterized in that: The current image is an image with a QVGA resolution or a QQVGA resolution.

10. An image recognition method, characterized in that: The method comprises: Acquire an image to be recognized, wherein the image is a corrected image obtained by the image processing method according to any one of claims 1 to 9; Image recognition is performed according to the image to be recognized to obtain an image recognition result.

11. The image recognition method according to claim 10, characterized in that: The performing image recognition according to the image to be recognized to obtain an image recognition result includes: Perform face recognition based on the image to be recognized to obtain a face recognition result.

12. The image recognition method according to claim 10, characterized in that: The performing image recognition according to the image to be recognized to obtain an image recognition result includes: Perform gaze recognition according to the image to be recognized, and obtain a gaze recognition result.

13. A control device, comprising at least one processor and at least one storage device, wherein the storage device is suitable for storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by the processor to execute the image processing method according to any one of claims 1 to 9 or the image recognition method according to any one of claims 10 to 12.

14. The image recognition method according to claim 13, characterized in that: The processor is a low power consumption processor.

15. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the image processing method according to any one of claims 1 to 9 or the image recognition method according to any one of claims 10 to 12.

16. A terminal device, characterized in that: The terminal device is provided with an image sensor and an ambient light sensor, and the terminal device includes the control device according to claim 13 or 14.

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