CN114626090A - Image data processing method and device and vehicle - Google Patents
Image data processing method and device and vehicle Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a method and a device for processing image data and a vehicle, wherein the processing method comprises the following steps: carrying out image restoration on the original image to obtain a three-channel image; if the three-channel image is in the image desensitization processing mode, performing image recognition on the three-channel image, and determining a sensitive image area in the three-channel image; determining a mask image of the three-channel image based on the sensitive image area; and performing data desensitization processing on the three-channel image based on the mask image. The embodiment of the disclosure can effectively protect the security of the privacy data in the image collected by the sensor.
Description
Technical Field
The present disclosure relates to computer vision technologies, and in particular, to a method and an apparatus for processing image data, and a vehicle.
Background
With the development of intelligent identification technology, data privacy issues gradually draw extensive attention. After the image data is collected by the image collecting device, how to ensure the security of the privacy data in the collected data is a problem to be solved urgently.
Disclosure of Invention
The present disclosure is proposed to solve the above technical problems. The embodiment of the disclosure provides a method and a device for processing image data and a vehicle.
According to a first aspect of the embodiments of the present disclosure, there is provided a method for processing image data, including:
carrying out image restoration on the original image to obtain a three-channel image;
if the three-channel image is in an image desensitization processing mode, performing image recognition on the three-channel image, and determining a sensitive image area in the three-channel image;
determining a mask image of the three-channel image based on the sensitive image area;
and carrying out data desensitization processing on the three-channel image based on the mask image.
According to a second aspect of the embodiments of the present disclosure, there is provided an apparatus for processing image data, including:
the image restoration module is used for carrying out image restoration on the original image to obtain a three-channel image;
the sensitive image area determining module is used for carrying out image recognition on the three-channel image if the three-channel image is in a normal image processing mode and determining a sensitive image area in the three-channel image;
the mask image determining module is used for determining a mask image of the three-channel image based on the sensitive image area;
and the desensitization module is used for performing data desensitization processing on the three-channel image based on the mask image.
According to a third aspect of the embodiments of the present disclosure, there is provided a vehicle including the image data processing apparatus according to the second aspect.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program for executing the method of processing image data according to the first aspect.
According to a fifth aspect of embodiments of the present disclosure, there is provided an electronic apparatus including:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instruction from the memory, and execute the instruction to implement the image data processing method according to the first aspect.
Based on the image data processing method, the image data processing device and the vehicle provided by the embodiment of the disclosure, after the original image is subjected to image restoration to obtain the three-channel image, if the original image is in the image desensitization processing mode, the three-channel image is subjected to image recognition to determine the sensitive image area in the three-channel image, the mask image of the three-channel image is determined based on the sensitive image area, and then the data desensitization processing is performed on the three-channel image based on the mask image, so that the security of the privacy data in the image acquired by the sensor can be effectively protected.
The technical solution of the present disclosure is further described in detail by the accompanying drawings and examples.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing in more detail embodiments of the present disclosure with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the principles of the disclosure and not to limit the disclosure. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 is a flow chart illustrating a method for processing image data according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart of step S3 in one embodiment of the present disclosure;
FIG. 3 is a schematic diagram of generating a mask image based on a three channel image in one example of the present disclosure;
FIG. 4 is a block diagram of an apparatus for processing image data according to an embodiment of the present disclosure;
FIG. 5 is a block diagram of a mask image determination module 300 according to one embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device provided in an exemplary embodiment of the present disclosure.
Detailed Description
Hereinafter, example embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are only some of the embodiments of the present disclosure, and not all of the embodiments of the present disclosure, and it is to be understood that the present disclosure is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
It will be understood by those of skill in the art that the terms "first," "second," and the like in the embodiments of the present disclosure are used merely to distinguish one element from another, and are not intended to imply any particular technical meaning, nor is the necessary logical order between them.
It is also understood that in embodiments of the present disclosure, "a plurality" may refer to two or more and "at least one" may refer to one, two or more.
It is also to be understood that any reference to any component, data, or structure in the embodiments of the disclosure, may be generally understood as one or more, unless explicitly defined otherwise or stated otherwise.
In addition, the term "and/or" in the present disclosure is only one kind of association relationship describing an associated object, and means that three kinds of relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the former and latter associated objects are in an "or" relationship.
It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and the same or similar parts may be referred to each other, so that the descriptions thereof are omitted for brevity.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
The disclosed embodiments may be applied to electronic devices such as terminal devices, computer systems, servers, etc., which are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as terminal devices, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.
Summary of the disclosure
In the course of implementing the present disclosure, the inventors found that three-channel images can be obtained by performing image restoration on a RAW image (i.e., RAW image) acquired by an image sensor, and then the three-channel images are stored. When the three-channel image includes a human image, human behavior recognition can be performed based on the stored three-channel image.
Since the three-channel image may include sensitive information such as face information, and desensitization processing is not performed on the sensitive information in the related art, but the three-channel image with the sensitive information is directly stored, there is a risk of sensitive information leakage.
Brief description of the drawings
In the disclosure, after the original image is subjected to image restoration to obtain the three-channel image, an image area of the sensitive information in the three-channel image, that is, a sensitive image area, may be determined by an image recognition technology. And selecting a mask image matched with the size of the three-channel image, and setting a numerical mask in a position corresponding to the sensitive image area in the mask image. Based on the position of the numerical mask in the mask image, the desensitization processing can be accurately carried out on the sensitive image area in the three-channel image, and then the three-channel image after the desensitization processing is stored, so that the three-channel image after the desensitization processing is used when the person behavior identification is carried out. By the method and the device, the three-channel image after desensitization can be stored, so that the security of sensitive information can be effectively included.
Exemplary method
Fig. 1 is a flowchart illustrating a method for processing image data according to an embodiment of the present disclosure. The embodiment can be applied to an electronic device, as shown in fig. 1, and includes the following steps:
s1: and carrying out image restoration on the original image to obtain a three-channel image.
The native image is acquired by an image sensor. For example, the RAW Image may be a RAW Image (RAW Image Format) of the driver collected by an Image sensor in the vehicle and not subjected to Image restoration in a state where the vehicle assistant driving function or the automatic driving function is turned on, or a RAW Image (RAW Image Format) including passenger information collected by an Image sensor in the vehicle and not subjected to Image restoration.
After the original image is acquired, the image restoration may be performed on the original image by the host vehicle control system or a terminal (e.g., a mobile phone or a server) that may be connected to control the host vehicle, so as to obtain a three-channel image corresponding to the original image. The three-channel image can be an RGB three-channel image or a YUV three-channel image.
R, G, and B channel images of the same size as the native image may be obtained using, but not limited to, bicubic interpolation.
The specific process of obtaining the R channel image by interpolation of the original image comprises the following steps: and the R channel pixel value corresponding to the B channel position on the interpolation native image and the R channel pixel value corresponding to the G channel position on the interpolation native image.
The specific process of obtaining the G channel image by interpolation of the native image comprises the following steps: and G channel pixel values corresponding to the B channel positions on the interpolation native images and G channel pixel values corresponding to the R channel positions on the interpolation native images.
The specific process of obtaining the B channel image by interpolation of the native image comprises the following steps: and B-channel pixel values corresponding to the R-channel positions on the interpolation native images and B-channel pixel values corresponding to the G-channel positions on the interpolation native images.
And finishing the interpolation step to obtain the R channel image, the G channel image and the B channel image with the same image size as the original image.
S2: and if the three-channel image is in the image desensitization processing mode, performing image recognition on the three-channel image, and determining a sensitive image area in the three-channel image.
In the present embodiment, the image processing mode includes an image normal processing mode and an image desensitization processing mode.
In the normal image processing mode, the three-channel image can be directly stored, or the three-channel image can be directly subjected to image analysis processing.
In the image desensitization processing mode, image recognition can be performed on the three-channel image through a pre-trained image recognition model, and a sensitive image area in the three-channel image, such as a face image area of a driver or a face image area of a passenger, can be determined through a detection frame and the like. The image recognition model can be trained based on the sample image and the recognition result label of the sample image.
S3: based on the sensitive image area, a mask image of the three-channel image is determined.
A mask image of the same size as the three channel image is used. The three-channel image and the mask image may be divided into a plurality of image blocks, for example, the three-channel image and the mask image are divided into (N × M) number of image blocks according to the same row-column division manner, where N and M are both natural numbers greater than 0.
In the mask image, the image blocks in the area corresponding to the sensitive image area in the three-channel image are set as preset mask values, so that when a certain image block of the mask image is read and set as the preset mask value, the image block corresponding to the three-channel image in the sensitive image area can be known.
S4: and carrying out data desensitization processing on the three-channel image based on the mask image.
When desensitization processing is carried out on a three-channel image, all image blocks which are set as preset mask values in the mask image are firstly obtained, then all corresponding image blocks in the three-channel image are obtained, and data desensitization processing is carried out through a preset data desensitization mode.
In the embodiment, after the original image is subjected to image restoration to obtain the three-channel image, if the three-channel image is in the image desensitization processing mode, the three-channel image is subjected to image recognition to determine the sensitive image area in the three-channel image, the mask image of the three-channel image is determined based on the sensitive image area, and then the data desensitization processing is performed on the three-channel image based on the mask image, so that the security of the private data in the image acquired by the sensor can be effectively protected.
Fig. 2 is a schematic flow chart of step S3 in an embodiment of the present disclosure. As shown in fig. 2, step S3 includes:
s3-1: and determining a first image area corresponding to the position of the sensitive image area in the mask image based on the position of the sensitive image area in the three-channel image.
Fig. 3 is a schematic diagram of generating a mask image based on a three-channel image in one example of the present disclosure. As shown in fig. 3, a mask image having the same size as the three-channel image is used to divide the three-channel image and the mask image into a plurality of image blocks. It should be noted that, although the three-channel image and the mask image are divided into 64 image blocks of 8 rows and 8 columns in this example, the embodiment does not limit the specific division manner of the image blocks, nor the specific division number of the image blocks.
And determining a first image area corresponding to the position of the sensitive image area in the mask image, namely the image area with the mask value of 1 in the mask image, based on the position of the sensitive image area in the three-channel image.
S3-2: the remaining image area of the mask image excluding the first image area is determined as a second image area, that is, an image area of the mask image in which the mask value is 0.
S3-3: a first numerical value is set for each unit image block in the first image area.
A first numerical value is set for a unit image block, and the unit image block corresponding to the unit image block in the three-channel image is represented to be in the sensitive image area. In the example shown in fig. 3, the first value is 1.
Further, the second numerical value may also be set for each unit image block in the second image area. A second value is set for a unit image block, and represents that the unit image block corresponding to the position of the unit image block in the three-channel image is outside the sensitive image area, and in the example shown in fig. 3, the second value is 0.
Accordingly, step S4 may include: based on the first numerical value, determining a desensitization image area corresponding to the position of the first image area in the three-channel image, namely acquiring all image blocks corresponding to the positions of the three-channel image according to the positions of all image blocks with mask values of 1 in the mask image, and further determining the desensitization image area needing desensitization; and performing data desensitization processing on the three-channel image based on the desensitization image area.
In this embodiment, after dividing the three-channel image and the mask image into a plurality of image blocks, setting a first numerical value or a second numerical value for different image blocks of the mask image, and representing the image block in the three-channel image that needs to be subjected to data desensitization and the image block that does not need to be subjected to data desensitization by using the different numerical values. When data desensitization is carried out on the three-channel image, the image blocks needing data desensitization in the three-channel image can be quickly determined according to the first numerical value in the mask image, so that the determined image blocks needing data desensitization are subjected to data desensitization.
In an embodiment of the disclosure, the step of performing data desensitization processing on the three-channel image based on the desensitization image region may include: and adjusting the pixel points in the desensitization image area in the three-channel image into target pixel values. The difference between the target pixel value and the pixel boundary value is within a preset difference range, for example, the preset difference range may be [0, 5 ].
In one example of the present disclosure, a pixel value range in the three-channel image is 0 to 255, a preset difference value range is [0, 5], and one pixel value is selected as a target pixel value in a preset interpolation range. The pixel points in the desensitization image area in the three-channel image are adjusted to be target pixel values, so that the sensitive information is hidden, and the security of the sensitive information is improved.
In this embodiment, all pixel values in the desensitization image region where the sensitive information exists in the three-channel image are set as the target pixel values, so that the sensitive information can be hidden, and the security of the sensitive information is improved.
In another embodiment of the present disclosure, the step of performing data desensitization processing on the three-channel image based on the desensitization image region may include: and carrying out image blurring processing on an image block in a desensitization image area in the three-channel image.
The sensitive area of the three-channel image can be blurred through a preset convolution kernel. The size of the preset convolution kernel and the weight distribution of the convolution kernel can be determined based on the security classification type of the object corresponding to the image desensitization area. If the classified type identifier of the object indicates that the object (such as the eye region of the driver in the raw image) needs to be highly confidential, the resolution of the convolution kernel may be set to be larger, and the weight of the convolution kernel needs to be set to have higher blurring strength, for example, the size of the preset convolution kernel may be 21 × 21, so as to ensure that the object in the sensitive region is prevented from being restored subsequently; if the security classification type identifier of the target object indicates that the security classification of the target object (for example, the forehead area of the driver in the raw image) is low, the resolution of the convolution kernel can be set to be small, and the weight of the convolution kernel needs to be set to have relatively weak blurring strength, for example, the size of the preset convolution kernel can be 5x 5.
In the embodiment, the image blurring processing is performed on the image block in the desensitized image area in the three-channel image, so that the user privacy can be effectively protected.
In an embodiment of the present disclosure, after step S1, the method may further include: and performing behavior detection on the target object in the three-channel image after the data desensitization treatment to obtain a behavior detection result of the target object.
In one example of the present disclosure, when the three-channel image includes a target object, the sensitive image region may include an eye region of the target object. After data desensitization processing, the eye region of the target object in the three-channel image can be hidden. By using the three-channel image after desensitization, smoking behavior detection can be performed on the target object aiming at the mouth image area and the hand image area of the target object, behavior detection whether the steering wheel is held by hands can be performed aiming at the hand image area of the target object, and behavior detection whether the safety belt is fastened can be performed aiming at the upper body image area of the target object.
In this embodiment, behavior detection is performed on the target object in the desensitized three-channel image, so that on the premise of ensuring security of private data, behavior detection based on the image is not affected, and user satisfaction is improved.
In another embodiment of the present disclosure, after step S1, the method may further include: and if the three-channel image is in the normal image processing mode, performing behavior detection on the target object in the three-channel image to obtain a behavior detection result of the target object.
In an example of the present disclosure, when the three-channel image includes a target object, smoking behavior detection may be performed on the target object with respect to a mouth image area and a hand image area of the target object, behavior detection may be performed on whether a steering wheel is held by a hand with respect to a hand image area of the target object, and behavior detection may be performed on whether a safety belt is fastened with respect to an upper body image area of the target object.
In this embodiment, when the image processing apparatus is in the normal image processing mode, data desensitization processing is not required to be performed on the three-channel image, and behavior detection can be directly performed on a target object in the three-channel image, so that the diversity of selection for whether to perform image desensitization processing is improved.
Any kind of image data processing method provided by the embodiments of the present disclosure may be executed by any suitable device with data processing capability, including but not limited to: terminal equipment, a server and the like. Alternatively, any image data processing method provided by the embodiments of the present disclosure may be executed by a processor, for example, the processor may execute any image data processing method mentioned in the embodiments of the present disclosure by calling a corresponding instruction stored in a memory. And will not be described in detail below.
Exemplary devices
Fig. 4 is a block diagram of a processing apparatus of image data according to an embodiment of the present disclosure. As shown in fig. 4, the image data processing apparatus includes:
the image restoration module 100 is configured to perform image restoration on the native image to obtain a three-channel image;
the sensitive image area determining module 200 is configured to perform image recognition on the three-channel image if the three-channel image is in the normal image processing mode, and determine a sensitive image area in the three-channel image;
a mask image determining module 300, configured to determine a mask image of the three-channel image based on the sensitive image region;
and the desensitization module 400 is configured to perform data desensitization processing on the three-channel image based on the mask image.
Fig. 5 is a block diagram of the mask image determination module 300 according to an embodiment of the present disclosure. As shown in fig. 5, the image data processing apparatus includes:
a first image area unit 310, configured to determine, based on a position of the sensitive image area in the three-channel image, a first image area in the mask image corresponding to the position of the sensitive image area;
a second image area unit 320, configured to determine a remaining image area of the mask image excluding the first image area as a second image area;
a value setting unit 330, configured to set a first value for each unit image block in the first image area;
the desensitization module 400 is configured to determine, based on a first numerical value, a desensitization image region corresponding to the first image region position in the three-channel image, and perform data desensitization processing on the three-channel image based on the desensitization image region.
In an embodiment of the present disclosure, the desensitization module 400 is configured to adjust a pixel point located in the desensitization image region in the three-channel image to be a target pixel value, where a difference between the target pixel value and a pixel boundary value is within a preset difference range.
In another embodiment of the present disclosure, the desensitization module 400 is configured to perform image blurring on image blocks located in the desensitization image area in the three-channel image.
In one embodiment of the present disclosure, the apparatus for processing image data may further include:
and the first behavior detection module is used for performing behavior detection on the target object in the three-channel image after data desensitization processing to obtain a behavior detection result of the target object.
In another embodiment of the present disclosure, the image data processing apparatus may further include:
and the second behavior detection module is used for performing behavior detection on the target object in the three-channel image if the target object is in the normal image processing mode to obtain a behavior detection result of the target object.
It should be noted that, the specific implementation of the image data processing apparatus according to the embodiment of the present disclosure is similar to the specific implementation of the image data processing method according to the embodiment of the present disclosure, and for specific reference, the detailed description is omitted for reducing redundancy.
Exemplary electronic device
Next, an electronic apparatus according to an embodiment of the present disclosure is described with reference to fig. 6. As shown in fig. 6, the electronic device includes one or more processors 10 and memory 20.
The processor 10 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
Memory 20 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer readable storage medium and executed by the processor 11 to implement the image data processing methods of the various embodiments of the present disclosure described above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.
In one example, the electronic device may further include: an input device 30 and an output device 40, which are interconnected by a bus system and/or other form of connection mechanism (not shown). The input device 30 may be, for example, a keyboard, a mouse, or the like. Output devices 40 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, among others.
For simplicity, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 6, omitting components such as buses, input/output interfaces, and the like. In addition, the electronic device may include any other suitable components, depending on the particular application.
Exemplary computer readable storage Medium
A computer-readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure will be described in detail with reference to specific details.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The block diagrams of devices, apparatuses, devices, systems involved in the present disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the apparatus, devices, and methods of the present disclosure, various components or steps may be broken down and/or re-combined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.
Claims (10)
1. A method of processing image data, comprising:
carrying out image restoration on the original image to obtain a three-channel image;
if the three-channel image is in an image desensitization processing mode, performing image recognition on the three-channel image, and determining a sensitive image area in the three-channel image;
determining a mask image of the three-channel image based on the sensitive image area;
and performing data desensitization processing on the three-channel image based on the mask image.
2. The method of claim 1, wherein the determining a mask image for the three channel image based on the sensitive image region comprises:
determining a first image area corresponding to the position of the sensitive image area in the mask image based on the position of the sensitive image area in the three-channel image;
determining a residual image area of the mask image, from which the first image area is removed, as a second image area;
setting a first numerical value for each unit image block in the first image area;
wherein the performing data desensitization processing on the three-channel image based on the mask image comprises:
determining a desensitization image region corresponding to the first image region position in the three-channel image based on the first numerical value;
and carrying out data desensitization processing on the three-channel image based on the desensitization image area.
3. The method of claim 2, wherein the performing data desensitization processing on the three-channel image based on the desensitization image region comprises:
and adjusting pixel points in the desensitization image region in the three-channel image into target pixel values, wherein the difference value between the target pixel values and the pixel boundary values is within a preset difference value range.
4. The method of claim 2, wherein the performing data desensitization processing on the three-channel image based on the desensitization image region comprises:
and carrying out image blurring processing on the image block positioned in the desensitization image area in the three-channel image.
5. The method according to any one of claims 1-4, further comprising, after said performing data desensitization processing on said three channel image based on said mask image:
and performing behavior detection on the target object in the three-channel image after data desensitization processing to obtain a behavior detection result of the target object.
6. The method according to any one of claims 1-4, further comprising, after said image restoration of the native image to obtain a three-channel image:
and if the three-channel image is in the normal image processing mode, performing behavior detection on the target object in the three-channel image to obtain a behavior detection result of the target object.
7. An apparatus for processing image data, comprising:
the image restoration module is used for carrying out image restoration on the original image to obtain a three-channel image;
the sensitive image area determining module is used for carrying out image recognition on the three-channel image and determining a sensitive image area in the three-channel image if the three-channel image is in an image normal processing mode;
the mask image determining module is used for determining a mask image of the three-channel image based on the sensitive image area;
and the desensitization module is used for performing data desensitization processing on the three-channel image based on the mask image.
8. A vehicle comprising the image data processing apparatus of claim 7.
9. A computer-readable storage medium storing a computer program for executing the image data processing method according to any one of claims 1 to 6.
10. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is used for reading the executable instructions from the memory and executing the instructions to realize the image data processing method of any one of the claims 1 to 6.
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