Image processing method and device, electronic equipment and storage medium

Abstract

The invention provides an image processing method and device, electronic equipment and a storage medium, and relates to the field of financial science and tech, and the method comprises the steps: carrying out the mass center analysis of an image region for a shot target image, and determining a plurality of first target region images in the target image; according to pre-generated first target watermark information, wavelet quantization modulation processing is carried out on the multiple first target area images, a modulation coefficient set of the multiple first target area images embedded with first target sub-watermark information is obtained, and the multiple embedded first target sub-watermark information forms the first target watermark information; performing inverse wavelet transform processing on each modulation coefficient set to obtain a plurality of second target area images which correspond to the first target area images and are consistent in centroid; and in the target image, updating the plurality of first target area images into corresponding second target area images to generate a target watermark image. According to the invention, the security of the image watermark information can be improved.

Description

Technical Field

[0001] The present application relates to the field of financial technology, and in particular to an image processing method, device, electronic device and storage medium. Background Art

[0002] In the related technology, some property insurance software can realize self-service claims. Specifically, you only need to upload the photos of the insured object in the specific interface of these software to automatically complete the claims process. This autonomous claims method has defects, that is, the photos themselves. Specifically, after being uploaded to the property insurance software, it is difficult for the property insurance software background to identify whether the photos are photos of the insured object. In other words, photos taken of the insured object can pass the claims, and edited fake photos can also pass the claims. These situations can actually be achieved by embedding watermark information in the photos themselves. However, these watermark information can be forged. When the watermark information in the used claims image is modified, it can be identified by the property insurance software background as a real photo, which makes the claims risk control more likely to fail. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to propose an image processing method, device, electronic device and storage medium, aiming to improve the security of image watermark information so as to reduce the probability of failure of claims risk control.

[0004] To achieve the above object, a first aspect of an embodiment of the present application proposes an image processing method, which is applied to a terminal and includes the following steps: Performing centroid analysis on the image area of ​​the captured target image, and determining a plurality of first target area images in the target image; According to the pre-generated first target watermark information, wavelet quantization modulation processing is performed on the plurality of first target area images respectively to obtain a plurality of modulation coefficient sets of the first target area images, wherein each of the modulation coefficient sets is embedded with the first target sub-watermark information, and the plurality of embedded first target sub-watermark information constitute the first target watermark information; Performing inverse wavelet transform processing on each of the modulation coefficient sets respectively to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; In the target image, a plurality of the first target area images are updated to corresponding second target area images to generate a target watermark image.

[0005] In some embodiments, performing centroid analysis on an image area of ​​the captured target image and determining a plurality of first target area images in the target image includes: Performing a regional image pixel distribution state analysis on the target image for a preset image size to obtain first pixel distribution state information of the target image; According to the first pixel distribution state information, a region image in a target state in the target image is determined as the first target region image, wherein the target state is a state in which the centroid of the region image remains unchanged before and after wavelet quantization modulation processing is performed.

[0006] In some embodiments, the performing wavelet quantization modulation processing on the plurality of first target area images respectively according to the pre-generated first target watermark information to obtain a modulation coefficient set of the plurality of first target area images includes: Determining a target embedding quantity of the first target area image; Performing information segmentation processing on the first target watermark information according to the target embedding quantity, to obtain the first target sub-watermark information corresponding to each of a plurality of first target area images; Generating quantization coefficients for the first target area images according to the first target sub-watermark information respectively corresponding to the plurality of first target area images, to obtain quantization coefficient sets respectively corresponding to the plurality of first target area images; For each of the first target area images, based on the first target sub-watermark information corresponding to the first target area image and the corresponding quantization coefficient set, the first target area image is subjected to wavelet quantization modulation processing to obtain the corresponding modulation coefficient set.

[0007] In one embodiment, the first target watermark information is segmented according to the target embedding quantity to obtain the first target sub-watermark information corresponding to each of the plurality of first target area images, including: Performing information segmentation processing on the first target watermark information according to the target embedding quantity to obtain a plurality of first target sub-watermark information; For each first target area image, the centroid of the first target area image is determined, and an association relationship is established between the centroid of the first target area image and one of the plurality of first target sub-watermark information.

[0008] To achieve the above object, a second aspect of an embodiment of the present application proposes an image processing method, which is applied to a server and includes the following steps: Get the target watermark image; Performing centroid analysis on the target watermark image for the image area to obtain a plurality of second target area images; Performing wavelet transform processing on the plurality of second target area images respectively to obtain a modulation coefficient set of the plurality of second target area images; Performing inverse wavelet quantization modulation processing on the modulation coefficient sets of the plurality of second target area images respectively to obtain second target sub-watermark information embedded in the plurality of modulation coefficient sets, and synthesizing the plurality of second target sub-watermark information to obtain second target watermark information in the target watermark image; The first target watermark information is obtained, and the second target watermark information is compared with the first target watermark information. When the second target watermark information is the same as the first target watermark information, it is determined that the target image corresponding to the target watermark image is the original image.

[0009] In some embodiments, performing centroid analysis on the target watermark image for the image area to obtain a plurality of second target area images includes: Performing a pixel distribution state analysis of a region image of a preset image size on the target watermark image to obtain second pixel distribution state information of the target watermark image; According to the second pixel distribution state information, a region image in a target state in the target watermark image is determined as the second target region image, wherein the target state is a state in which the region image performs wavelet quantization modulation processing and the centroid remains unchanged.

[0010] In some embodiments, the performing inverse wavelet quantization modulation processing on the modulation coefficient sets of the plurality of second target area images respectively to obtain the second target sub-watermark information embedded in the plurality of modulation coefficient sets, and performing information synthesis on the plurality of second target sub-watermark information to obtain the second target watermark information in the target watermark image includes: Acquire a plurality of quantization coefficient sets corresponding to the second target area images respectively; For each second target area image, determining corresponding second target sub-watermark information from the modulation coefficient set of the second target area image by using the quantization coefficient set corresponding to the second target area image; The plurality of second target sub-watermark information are integrated to obtain the second target watermark information.

[0011] To achieve the above-mentioned purpose, a third aspect of an embodiment of the present application provides an image processing device, including: A first target area image acquisition module, configured to perform centroid analysis on the captured target image for the image area, and determine a plurality of first target area images in the target image; a watermark embedding module, configured to perform wavelet quantization modulation processing on a plurality of first target area images respectively according to pre-generated first target watermark information, so as to obtain a plurality of modulation coefficient sets of the first target area images, wherein each of the modulation coefficient sets is embedded with first target sub-watermark information, and a plurality of embedded first target sub-watermark information constitute the first target watermark information; A second target area image acquisition module, configured to perform inverse wavelet transform processing on each of the modulation coefficient sets to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; The target watermark image generating module is used to update the plurality of the first target area images into the corresponding second target area images in the target image, so as to generate a target watermark image.

[0012] To achieve the above objectives, the fourth aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0013] To achieve the above objectives, the fifth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0014] The present application proposes an image processing method, device, electronic device and storage medium, the method comprising performing centroid analysis on an image area of ​​a captured target image, and determining a plurality of first target area images in the target image; performing wavelet quantization modulation processing on the plurality of first target area images according to pre-generated first target watermark information, and obtaining a plurality of modulation coefficient sets of the first target area images, wherein each of the modulation coefficient sets is embedded with first target sub-watermark information, and a plurality of embedded first target sub-watermark information constitute the first target watermark information; performing inverse wavelet transform processing on each of the modulation coefficient sets, and obtaining a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; in the target image, updating the plurality of first target area images to the corresponding second target area image to generate a target watermark image. Through centroid analysis, multiple first target area images in the target image that can keep the centroid unchanged before and after wavelet quantization modulation processing can be determined, and then the first target sub-watermark information is embedded in these first target area images. Since the first target area image can keep the centroid unchanged before and after the wavelet quantization modulation processing, the first target area image can stably carry the first target sub-watermark information after the wavelet quantization modulation processing. In this way, the first target watermark information can be carried in the target watermark image more stably and more dispersedly, so that when it is necessary to forge the watermark information in the target image, it is necessary to find and modify the first target area images in multiple positions, thereby greatly improving the difficulty of forging the first target watermark information in the target image, which is conducive to reducing the impact on the authenticity of the watermark information by editing the image to forge the watermark information, thereby improving the authenticity and security of the watermark information. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of an image processing method provided by an embodiment of the present application; Figure 2 yes Figure 1 A flowchart of an embodiment of a sub-step of step 110; Figure 3 yes Figure 1 A flowchart of an embodiment of a sub-step of step 120; Figure 4 yes Figure 3 A flowchart of an embodiment of a sub-step of step 320; Figure 5 is a flowchart of an image processing method provided by another embodiment of the present application; Figure 6 yes Figure 5A flowchart of an embodiment of a sub-step of step 520; Figure 7 yes Figure 5 A flowchart of an embodiment of a sub-step of step 540; Figure 8 is a structural schematic diagram of an image processing device provided in an embodiment of the present application; Fig. 9 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0017] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0019] First, some nouns involved in this application are analyzed: Artificial intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. AI is a branch of computer science that attempts to understand the essence of intelligence and produce a new type of intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing and expert systems. AI can simulate the information process of human consciousness and thinking. AI is also a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0020] In the relevant technology, the autonomous claims settlement methods of some property insurance software are defective. Specifically, after uploading the claim pictures to the property insurance software, it is difficult for the background of the property insurance software to identify whether the pictures are actually taken of the insured object. In other words, pictures taken of the insured object can be passed for claims, and so can edited fake pictures or pictures directly generated by artificial intelligence models. This makes it easier for claims risk control to fail.

[0021] In order to improve the authenticity of the image and reduce the probability of failure of claims risk control, the present application provides an image processing method, an image processing device, an electronic device and a computer-readable storage medium, the method comprising performing a centroid analysis on the image area of ​​the captured target image, and determining multiple first target area images in the target image; performing wavelet quantization modulation processing on the multiple first target area images according to the pre-generated first target watermark information, and obtaining a modulation coefficient set of the multiple first target area images, wherein each of the modulation coefficient sets is embedded with the first target sub-watermark information, and the multiple embedded first target sub-watermark information constitute the first target watermark information; performing inverse wavelet transform processing on each of the modulation coefficient sets, and obtaining second target area images corresponding to the multiple first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; in the target image, updating the multiple first target area images to the corresponding second target area image to generate a target watermark image. Through centroid analysis, multiple first target area images in the target image that can keep the centroid unchanged before and after wavelet quantization modulation processing can be determined, and then the first target sub-watermark information is embedded in these first target area images. Since the first target area image can keep the centroid unchanged before and after the wavelet quantization modulation processing, the first target area image can stably carry the first target sub-watermark information after the wavelet quantization modulation processing. The first target watermark information can be carried in the target watermark image more stably and more dispersedly, so that when it is necessary to forge the watermark information in the target image, it is necessary to find and modify the first target area images in multiple positions, thereby greatly improving the difficulty of forging the first target watermark information in the target image, which is conducive to reducing the impact on the authenticity of the watermark information by editing the image to forge the watermark information, thereby improving the authenticity and security of the watermark information.

[0022] An image processing method, device, electronic device and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the image processing method in the embodiments of the present application is described.

[0023] The image processing method provided in the embodiment of the present application relates to the field of financial technology. The image processing method provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the image processing method, etc., but is not limited to the above forms.

[0024] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0025] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0026] See also Figure 1 , Figure 1 The figure shows the process of an image processing method provided by an embodiment of the present application. Figure 1The image processing method shown can be applied to a terminal. In this embodiment, the image processing method may include steps 110 to 140.

[0027] Step 110: performing centroid analysis on the captured target image for the image area, and determining a plurality of first target area images in the target image; Step 120: performing wavelet quantization modulation processing on a plurality of first target region images respectively according to the pre-generated first target watermark information to obtain a plurality of modulation coefficient sets of the first target region images, wherein each modulation coefficient set is embedded with the first target sub-watermark information, and the plurality of embedded first target sub-watermark information constitute the first target watermark information; Step 130: performing inverse wavelet transform processing on each modulation coefficient set to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; Step 140: In the target image, multiple first target area images are updated to corresponding second target area images to generate a target watermark image.

[0028] In one embodiment, the captured target image refers to an image captured directly by calling a camera in the software when a specific software running on the terminal needs to obtain an image to perform a certain function. The called camera can be a camera built into the terminal (such as a mobile phone camera), or a camera connected to the terminal (such as an external camera connected to a computer), etc., which is not specifically limited here. For example, when a financial software is running on a mobile phone, it is necessary to use a picture as evidence for a claim. In the claim interface of the software, there is a shooting area. When the area is clicked, the software can call the camera of the mobile phone to take a picture and perform subsequent functions or steps. The picture taken here is the target image.

[0029] In one embodiment, the centroid analysis for an image region refers to a process of analyzing whether the centroid of a region of a preset size on an image will shift after the wavelet coefficient of the centroid of the region is changed to embed watermark information. It should be noted that the centroid analysis can be performed by wavelet transform or not, which is not specifically limited here.

[0030] In one embodiment, in the process of performing centroid analysis on the image area of ​​the captured target image and determining multiple first target area images in the target image, specifically, for each area image of a preset image size in the target image, the area image may be first normalized, and then the normalized area image may be subjected to wavelet transform to obtain a set of wavelet coefficients before the transform, and then the wavelet coefficients in the wavelet coefficient set may be updated using a preset wavelet coefficient quantization test coefficient (i.e., quantization index modulation (QIM)) to obtain a set of wavelet coefficients after the transform, and the centroids corresponding to the wavelet coefficient set before and after the transform are calculated respectively according to the wavelet coefficient set before and after the transform, and when the centroids corresponding to the wavelet coefficient set before and after the transform remain unchanged, the area image is determined as the first target area image. The preset image size refers to the size of an area image. In addition, the image normalization process can be a normalization process based on moments, or a normalization process based on gray levels, etc., in which moments can be one of the specific moments such as central moments, normalized moments, and central normalized moments, which are not specifically limited here. In addition, the wavelet coefficient set refers to a coefficient set of one or more of the multiple sub-bands obtained by wavelet transform processing, which can specifically include one or more of the approximate sub-bands (Low-Low, LL), horizontal detail sub-bands (Low-High, LH), vertical detail sub-bands (High-Low, HL), and diagonal detail sub-bands (High-High, HH), which are not specifically limited here.

[0031] In one embodiment, the first target region image refers to the original region image of the target image, which keeps the centroid unchanged after being modified by its corresponding wavelet coefficients. The sizes of the multiple first target region images may be the same or different, which is not specifically limited here.

[0032] In one embodiment, the first target watermark information refers to a type of information that is embedded in an image to prove that the image is a target image captured by a camera called by specific software, and after being embedded, it can be non-visualized in the target image. Among them, being non-visualized in the target image means that before and after the first target watermark information is embedded in the target image, the target image will not visually change in plaintext properties (such as directly synthesizing a text watermark in the target image). In addition, the first target watermark information can be specific information (such as user ID, user-defined real number, etc.), or attribute information at the time of shooting (such as a timestamp formed by the specific time when the target image is shot, software version number, mobile phone number, etc.), etc., which is not specifically limited here.

[0033] In one embodiment, in the process of pre-generating the first target watermark information, the first information to be processed used as the watermark information can be obtained first, and then the first information to be processed is encrypted by a preset encryption algorithm to obtain the first target watermark information. The encryption algorithm can be an SM4 encryption algorithm, or an Advanced Encryption Standard (AES) algorithm, etc., which is not specifically limited here. By using encrypted information to generate watermark information, when the image information is embedded in the target image, the security of the watermark information can be improved, thereby reducing the possibility of the watermark information being tampered with by the outside.

[0034] In one embodiment, performing wavelet quantization modulation processing on the first target area image refers to determining the wavelet coefficient quantization coefficients used for the first target area image according to the first target sub-watermark information, and using the wavelet coefficient quantization coefficients to QIM the wavelet coefficients in the wavelet coefficient set corresponding to the obtained first target area image to embed the watermark information. Among them, the wavelet coefficients in the wavelet coefficient set corresponding to the first target area image can be a coefficient set through a layer of wavelet transformation, or a coefficient set through multiple layers of wavelet transformation, which is not specifically limited here. In addition, the first target sub-watermark information refers to the segmentation information in the first target watermark information. For example, assuming that the first target watermark information is "1234567812345", then "1234", "5678" and "12345" all belong to the first target sub-watermark information of this first target watermark information.

[0035] In one embodiment, when the centroid analysis of the image area of ​​the captured target image is performed by wavelet transform, the obtained wavelet coefficient set can be directly called in the process of performing wavelet quantization modulation processing on the first target area image; when the centroid analysis of the image area of ​​the captured target image is not performed by wavelet transform, in the process of performing wavelet quantization modulation processing on the first target area image, the first target area image can be firstly subjected to wavelet transform processing to obtain the wavelet coefficient set corresponding to the first target area image.

[0036] In one embodiment, performing inverse wavelet transform on the modulation coefficient set refers to a process of generating a second target area image by performing inverse wavelet transform on the modulation coefficient set. The modulation coefficient set refers to a wavelet coefficient set corresponding to the first target area image obtained after QIM. In addition, the second target area image refers to an image of the first target area image after the first target sub-watermark information is embedded.

[0037] In one embodiment, in the process of updating each first target area image to the corresponding second target area image to generate the target watermark image, for each first target area image, the first target area image and its corresponding second target area image are specifically paired in pixel position, the pixel corresponding to each pixel in the first target area image in the corresponding second target area image is determined, and each pixel in the first target area image is replaced with the corresponding pixel in the second target area image to update the first target area image to the second target area image. The target watermark image refers to the image after the first target watermark information is embedded in the target image.

[0038] See also Figure 2 , Figure 2 Shows Figure 1 In one embodiment, step 110 may not perform centroid analysis by wavelet transform. Specifically, step 110 may include the following steps.

[0039] Step 210: performing a pixel distribution state analysis on a region image of a preset image size on the target image to obtain first pixel distribution state information of the target image; Step 220: According to the first pixel distribution state information, a region image in a target state in the target image is determined as a first target region image, wherein the target state is a state in which the centroid of the region image remains unchanged before and after the wavelet quantization modulation processing is performed.

[0040] In one embodiment, the pixel distribution state analysis of the regional images of the preset image size to obtain the first pixel distribution state information of the target image refers to the operation of dividing the target image into a plurality of regional images according to the preset image size, analyzing the distribution state of various pixel values ​​in each regional image one by one, and obtaining the first pixel distribution state information. The pixel distribution state analysis of each regional image can be performed by calculating the variance, histogram, grayscale entropy, etc. of the pixel values, which are not specifically limited here. In addition, the first pixel distribution state information refers to information used to represent the pixel distribution state of all regional images of the target image. In addition, the regional image pixel distribution state analysis can analyze whether the distribution state of the pixel values ​​in the regional image is a uniform distribution state, or whether the distribution state of the pixel values ​​is a symmetrical distribution state, etc., which are not specifically limited here.

[0041] In one embodiment, multiple preset image sizes may be preset. After determining the first target area image, if the number of first target area images determined under the current preset image size is not greater than 1, a relatively largest preset image size that is smaller than the current preset image size among multiple preset image sizes is selected to re-execute steps 210 to 220.

[0042] By analyzing the regional pixel distribution status of each regional image, the distribution status of the regional image pixels can be quickly determined. Since the invariance of the center of mass is closely related to the pixel distribution of the image, whether the center of mass of the regional image can remain unchanged before and after the wavelet quantization modulation processing can be quickly determined based on the distribution status of the regional image pixels. Therefore, there is no need to calculate the center of mass to determine whether the center of mass can remain unchanged before and after the wavelet quantization modulation processing, which is conducive to quickly and more accurately determining the first target regional image with higher information carrying stability.

[0043] Reference Figure 3 , Figure 3 Shows Figure 1 In one embodiment, step 120 may include steps 310 to 340.

[0044] Step 310: Determine the target embedding quantity of the first target area image; Step 320: performing information segmentation processing on the first target watermark information according to the target embedding quantity, and obtaining first target sub-watermark information corresponding to each of the plurality of first target region images; Step 330: generating quantization coefficients for the first target area images according to the first target sub-watermark information corresponding to each of the plurality of first target area images, and obtaining quantization coefficient sets corresponding to each of the plurality of first target area images; Step 340: For each first target region image, based on the corresponding first target sub-watermark information and the quantization coefficient corresponding to the first target sub-watermark information, perform wavelet quantization modulation processing on the first target region image to obtain a corresponding modulation coefficient set.

[0045] In one embodiment, in the process of determining the target embedding quantity of the first target area image, specifically, the information segmentation capability analysis can be first performed based on the first target watermark information to obtain the information segmentation capability analysis result, and the target embedding quantity is determined based on the information segmentation capability analysis result and the actual number of the first target area images. Among them, the information segmentation capability analysis refers to the process of analyzing the limit of the segmentation of the first target watermark information when it is information segmented. In addition, the target embedding quantity refers to the number of first target area images actually used to embed the first target sub-watermark information, among which, when the actual number of first target area images is greater than the segmentation limit number of the first target watermark information, the target embedding quantity is equal to the number of the first target sub-watermark information, and when the actual number of first target area images is less than the segmentation limit number of the first target watermark information, the target embedding quantity can be less than or equal to the actual number of first target area images.

[0046] In one embodiment, when the first target watermark information is composed of information of multiple attributes, and the number of attribute types is less than the actual number of the first target area image, the target embedding quantity is determined as the number of attribute types.

[0047] In one embodiment, performing information segmentation processing on the first target watermark information according to the target embedding quantity to obtain the first target sub-watermark information corresponding to each of the plurality of first target region images refers to segmenting the first target watermark information into the first target sub-watermark information of the target embedding quantity, and assigning one of the plurality of first target sub-watermark information to each of the plurality of first target region images. In the process of assigning the first target sub-watermark information to a first target region image, a sequence number may be firstly set for each first target region image, and then the sequence number of a first target region image is bound to a first target sub-watermark information.

[0048] In one embodiment, for the generation of quantization coefficients of the first target area image, obtaining the quantization coefficient sets corresponding to each of the multiple first target area images means that a quantization coefficient set corresponding only to the first target area image is generated according to the first target sub-watermark information corresponding to the first target area image, wherein the quantization coefficient set refers to a set consisting of multiple quantization coefficients, and one of the multiple quantization coefficients corresponds to the first target sub-watermark information. Specifically, in a target image, different first target area images use different quantization coefficients for wavelet quantization modulation processing, which makes the quantization coefficients used by different target images completely different. When watermark information comparison is required, one target image cannot use the quantization coefficients of other target images to extract watermark information, thereby improving the target watermark image's resistance to geometric attacks. Among them, the quantization coefficient corresponding to the first target area image can be associated with the centroid of the first target area image.

[0049] For example, there are first target area images A and B in the target image, the first target area image A is assigned the first target sub-watermark information A1, and the first target area image B is assigned the first target sub-watermark information B1. At this time, quantization coefficients 150 and 160 are generated for the first target area image A according to the first target sub-watermark information A1, 150 corresponds to A1, and 160 corresponds to 0. Then, 150 and 160 constitute a set of quantization coefficients specifically generated for the first target area image A. Similarly, quantization coefficients 160 and 170 are generated for the first target area image B according to the first target sub-watermark information B1, 160 corresponds to B1, and 170 corresponds to 0. Then, 160 and 170 constitute a set of quantization coefficients specifically generated for the first target area image B. Set, assuming that the modulation coefficient sets of the first target area images A and B are to be subjected to wavelet quantization modulation processing, then the modulation coefficient set of the first target area image A will only be quantized using the quantization coefficient set corresponding to the first target area image A, that is, some wavelet coefficients in the modulation coefficient set of the first target area image A will be quantized to 150, and the modulation coefficient set of the first target area image B will only be quantized using the quantization coefficient set corresponding to the first target area image B, that is, some wavelet coefficients in the modulation coefficient set of the first target area image B will be quantized to 160. Although the specially generated quantization coefficients used by both are 160, the first target sub-watermark information corresponding to the two in their respective first target area images is different.

[0050] By generating an independent quantization coefficient set for each first target area image, each first target area image can be quantized using an exclusive quantization coefficient set, so that the first target sub-watermark information in each first target area image can improve the ability of each first target area image to resist geometric attacks. In this way, when it is necessary to forge the watermark information in the target image, it is first necessary to know the quantization coefficient set corresponding to each first target area image that needs to be modified, so that the difficulty of forging the first target watermark information in the target image can be further improved, thereby better improving the authenticity and security of the watermark information.

[0051] See also Figure 4 , Figure 4 Shows Figure 3 In one embodiment, step 320 may include the following steps.

[0052] Step 410: performing information segmentation processing on the first target watermark information according to the target embedding quantity to obtain a plurality of first target sub-watermark information; Step 420: For each first target region image, determine the centroid of the first target region image, and establish an association relationship between the centroid of the first target region image and one of the plurality of first target sub-watermark information.

[0053] In one embodiment, establishing an association relationship between the centroid of the first target region image and one of the multiple first target sub-watermark information refers to an operation of associating the specific coordinates of the centroid of the first target region image in the target image with one of the multiple first target sub-watermark information. The first target sub-watermark information associated with the centroid of a target region image may be a random unassociated first target sub-watermark information among the multiple first target sub-watermark information, or may be an unassociated first target sub-watermark information carrying specific attribute information among the multiple first target sub-watermark information, and so on, which is not specifically limited here.

[0054] In one embodiment, the association relationship corresponding to the centroid of each first target area image may be stored in a mapping table or in a plain text format, which is not specifically limited here.

[0055] By constructing the association relationship between the centroid of the first target area image and the first target sub-watermark information, the first target area image can be assigned the corresponding first target sub-watermark information, so that the quantization coefficient set generated based on the first target sub-watermark information can be bound to the first target area image, and then the first target area image can be conveniently and accurately quantized using the exclusive quantization coefficient set. In addition, this binding method can make it easier for the server to determine the quantization coefficient set used when extracting watermark information, making the extraction of watermark information faster.

[0056] See also Figure 5 , Figure 5 The figure shows the process of an image processing method provided by another embodiment of the present application. Figure 5 The image processing method shown can be applied to a server. In this embodiment, the image processing method can include steps 510 to 540.

[0057] Step 510: Obtain a target watermark image; Step 520: performing centroid analysis on the target watermark image for the image area to obtain a plurality of second target area images; Step 530: performing wavelet transform processing on the plurality of second target area images respectively to obtain a modulation coefficient set of the plurality of second target area images; Step 540: performing inverse wavelet quantization modulation processing on the modulation coefficient sets of the multiple second target area images respectively to obtain the second target sub-watermark information embedded in the multiple modulation coefficient sets, and synthesizing the multiple second target sub-watermark information to obtain the second target watermark information in the target watermark image; Step 550: Acquire the first target watermark information, compare the second target watermark information with the first target watermark information, and when the second target watermark information is the same as the first target watermark information, determine that the target image corresponding to the target watermark image is the original image.

[0058] In one embodiment, the centroid analysis process for the image area of ​​the target watermark image corresponds to the centroid analysis process for the image area of ​​the captured target image. When the centroid analysis process of the target image is performed by wavelet transform, the centroid analysis process of the target watermark image is also performed by wavelet transform, and the number of wavelet transform layers between the two is the same; when the centroid analysis process of the target image is not performed by wavelet transform, the centroid analysis process of the target watermark image is also not performed by wavelet transform, and no specific limitation is made here.

[0059] In one embodiment, in the process of performing centroid analysis on the target watermark image for the image area to obtain multiple second target area images, specifically, for each area image of the preset image size in the target watermark image, the area image may be first normalized, and then the normalized area image may be subjected to wavelet transform processing to obtain a wavelet coefficient set before the transform, and then the wavelet coefficients in the wavelet coefficient set are updated using a preset wavelet coefficient quantization test coefficient to obtain a wavelet coefficient set after the transform, and the centroid corresponding to the wavelet coefficient set before and after the transform is calculated according to the wavelet coefficient set before the transform and the wavelet coefficient set after the transform, respectively, when the centroid corresponding to the wavelet coefficient set before and after the transform remains unchanged, the area image is determined as the second target area image. Wherein, the preset image size refers to the size of an area image. In addition, the image normalization processing may correspond to a normalization processing based on moments, or may correspond to a normalization processing based on gray levels, etc., which is not specifically limited here. In addition, the wavelet coefficient set may correspond to one or more of an approximate subband, a horizontal detail subband, a vertical detail subband, and a diagonal detail subband, which is not specifically limited here.

[0060] In one embodiment, in the process of performing wavelet transform processing on each second target area image respectively, the number of wavelet transform layers used by the terminal when performing wavelet quantization modulation processing on multiple first target area images respectively can be determined first, and then, wavelet transform processing can be performed on each second target area image respectively according to the number of wavelet transform layers.

[0061] In one embodiment, performing inverse wavelet quantization modulation processing on the modulation coefficient set of the second target area image refers to an operation of determining the corresponding watermark information (i.e., the second target sub-watermark information of the second target area image) through the wavelet coefficients of the modulation coefficient set based on the correspondence between the wavelet coefficient quantization coefficients and the watermark information.

[0062] In one embodiment, obtaining the first target watermark information can be achieved by direct reception (for example, sending a request to the terminal to obtain the first target watermark information), or by calling (for example, the terminal uploads the first target watermark information to the server after generating it, and the server can directly call it when using it), etc., which is not specifically limited here.

[0063] In one embodiment, the comparison between the second target watermark information and the first target watermark information can be a direct comparison or a comparison of decrypted information. For example, the encryption algorithm used by the terminal when encrypting the first target watermark information is first determined, and then the decryption algorithm corresponding to the encryption algorithm is determined. Then, the second target watermark information and the first target watermark information are decrypted simultaneously according to the decryption algorithm, and then the decrypted information of the second target watermark information is compared with the decrypted information of the first target watermark information. No specific limitation is made here.

[0064] In one embodiment, when the second target watermark information is different from the first target watermark information, it is determined that the target image corresponding to the target watermark image is a non-original image. There are various reasons why the second target watermark information is different from the first target watermark information, for example, the second target watermark information and the first target watermark information have the same length but different contents, or the second target watermark information of the target area image embedded with the target sub-watermark information is not fully recognized, resulting in the second target watermark information and the first target watermark information having different lengths, etc., which are not specifically limited here.

[0065] In one embodiment, after the server verifies that the target image corresponding to the target watermark image is the original image or the non-original image, different corresponding strategies can be executed. For example, when the target image corresponding to the target watermark image is the original image, the server can complete the claim processing. When the target image corresponding to the target watermark image is the non-original image, the server can complete the business risk control processing of fraudulent claims.

[0066] Since the target watermark image generated by the terminal can embed the second target sub-watermark information in multiple second target area images, the target watermark image can more stably carry watermark information that is more difficult to forge. By performing the second target sub-watermark information on multiple second target area images and integrating them, it can be determined whether the watermark information in the target watermark image is forged, and thus it can be determined whether the target image is a truly captured image that has not been edited with forged watermark information.

[0067] See also Figure 6 , Figure 6 Shows Figure 5 In one embodiment, step 520 may perform centroid analysis without wavelet transform. Specifically, step 520 may include the following steps.

[0068] Step 610: Analyze the pixel distribution state of the target watermark image in a region with a preset image size to obtain second pixel distribution state information of the target watermark image; Step 620: According to the second pixel distribution state information, determine the area image in the target state in the target watermark image as the second target area image, wherein the target state is a state in which the area image performs wavelet quantization modulation processing and the centroid remains unchanged.

[0069] In one embodiment, the pixel distribution state analysis for a preset image size to obtain the second pixel distribution state information of the target watermark image refers to the operation of dividing the target watermark image into a plurality of regional images according to the preset image size, analyzing the distribution state of various pixel values ​​in each regional image one by one, and obtaining the second pixel distribution state information. The pixel distribution state analysis of each regional image can be performed by calculating the variance, histogram, grayscale entropy, etc. of the pixel values, which is not specifically limited here. In addition, the second pixel distribution state information refers to information used to represent the pixel distribution state of all regional images of the target watermark image. In addition, the regional image pixel distribution state analysis can correspond to analyzing whether the distribution state of the pixel values ​​in the regional image is a uniform distribution state, or whether the distribution state of the pixel values ​​is a symmetrical distribution state, etc., which is not specifically limited here.

[0070] In one embodiment, in the process of performing regional image pixel distribution status analysis on the target watermark image for a preset image size to obtain the second pixel distribution status information of the target watermark image, the preset image size used in step 220 when finally determining the first target regional image can be specifically determined, and the regional image pixel distribution status analysis is performed based on the preset image size.

[0071] See also Figure 7 , Figure 7 Shows Figure 5 In one embodiment, step 540 may include the following steps.

[0072] Step 710: Obtain quantization coefficient sets corresponding to each of the plurality of second target area images; Step 720: for each second target area image, determine corresponding second target sub-watermark information from the modulation coefficient set of the second target area image through the quantization coefficient set corresponding to the second target area image; Step 730: Integrate the multiple second target sub-watermark information to obtain second target watermark information.

[0073] In one embodiment, for the modulation coefficient set of the second target area image, determining the corresponding second target sub-watermark information based on the quantization coefficient corresponding to the modulation coefficient set refers to comparing the quantization coefficient specifically corresponding to the second target area image with some specific wavelet coefficients in the modulation coefficient set to determine the second target sub-watermark information.

[0074] For example, there are first target area images A and B in the target image, the first target area image A is assigned the first target sub-watermark information A1, and the first target area image B is assigned the first target sub-watermark information B1. At this time, quantization coefficients 150 and 160 are generated for the first target area image A according to the first target sub-watermark information A1, 150 corresponds to A1, and 160 corresponds to 0. Then, 150 and 160 constitute a quantization coefficient set specifically corresponding to the first target area image A. Similarly, quantization coefficients 160 and 170 are generated for the first target area image B according to the first target sub-watermark information B1, and 160 corresponds to 0. B1, 170 corresponds to 0, then 160 and 170 constitute a quantization coefficient set specifically generated for the first target area image B. Assuming that the modulation coefficient sets of the first target area images A and B are now to be subjected to wavelet quantization modulation processing, then the modulation coefficient set of the first target area image A will only be quantized using the quantization coefficient set corresponding to the first target area image A, that is, some wavelet coefficients in the modulation coefficient set of the first target area image A will be quantized to 150, while the modulation coefficient set of the first target area image B will only be quantized using the quantization coefficient set corresponding to the first target area image B.

[0075] Assume that the first target region image A is embedded with the first target sub-watermark information A1 and becomes the second target region image C, and the first target region image B is embedded with the first target sub-watermark information B1 and becomes the second target region image D. For the second target region image C, the quantization coefficient set corresponding to the first target region image A (i.e., 150 and 160, where 150 corresponds to A1 and 160 corresponds to 0) is used to determine that the second target sub-watermark information is A1; for the second target region image D, the quantization coefficient set corresponding to the first target region image B (i.e., 160 and 170, where 160 corresponds to B1 and 170 corresponds to 0) is used to determine that the second target sub-watermark information is B1.

[0076] In one embodiment, in the process of determining the corresponding second target sub-watermark information based on the quantization coefficient corresponding to the modulation coefficient set for each second target area image, specifically, the center of mass of each second target area image can be first determined, and then the quantization coefficient corresponding to each second target area image can be determined based on the center of mass of each second target area image, and then the quantization coefficient corresponding to each second target area image can be used to extract the second target sub-watermark information from the corresponding modulation coefficient set.

[0077] By obtaining the quantization coefficient sets corresponding to multiple second target area images, the multiple second target area images can use their respective corresponding quantization coefficient sets to extract watermark information. Since the quantization coefficient sets correspond to the second target area images, the second target sub-watermark information in the second target area images can have strong independence. Therefore, the differences between the second target sub-watermark information in the multiple second target area images are relatively large, which makes it easier for the second target watermark information to prove whether it has been forged.

[0078] The following is an application example of the image processing method provided by the present application. Assuming that a property insurance software needs to put a picture used in the claims business that is manually modified or generated by artificial intelligence, the image can be photographed through the claims interface. At this time, the terminal can first perform a centroid analysis on the captured claims image for the image area, and determine multiple first target area images in the claims image. Then, according to the pre-generated first target watermark information, the multiple first target area images are respectively subjected to wavelet quantization modulation processing to obtain a modulation coefficient set of the multiple first target area images, wherein each modulation coefficient set is embedded with the first target sub-watermark information, and the multiple embedded first target sub-watermark information constitute the first target watermark information. Then, each modulation coefficient set is respectively subjected to inverse wavelet transform processing to obtain the second target area image corresponding to each first target area image, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image, and then, in the target image, each first target area image is updated to the corresponding second target area image to generate a claims watermark image.

[0079] The terminal can upload the claim watermark image to the server, and the server can first obtain the claim watermark image, then perform centroid analysis on the claim watermark image for the image area to obtain multiple second target area images, then perform wavelet transform processing on the multiple second target area images respectively to obtain modulation coefficient sets of the multiple second target area images, then perform inverse wavelet quantization modulation processing on the modulation coefficient sets of the multiple second target area images respectively to obtain the second target sub-watermark information embedded in the multiple modulation coefficient sets, perform information synthesis on the multiple second target sub-watermark information to obtain the second target watermark information in the target watermark image, then obtain the first target watermark information, compare the second target watermark information with the first target watermark information, and when the second target watermark information is the same as the first target watermark information, determine that the claim image corresponding to the claim watermark image is the original image. When the server determines that the claim image is the original image, it can execute the claim service.

[0080] See also Figure 8 The embodiment of the present application further provides an image processing device, which can implement the image processing method of the first aspect. The image processing device 800 includes: The first target area image acquisition module 810 may be used to perform centroid analysis on the captured target image for the image area, and determine a plurality of first target area images in the target image; The watermark embedding module 820 may be configured to perform wavelet quantization modulation processing on a plurality of first target region images respectively according to the pre-generated first target watermark information, so as to obtain a plurality of modulation coefficient sets of the first target region images, wherein each of the modulation coefficient sets is embedded with the first target sub-watermark information, and a plurality of the embedded first target sub-watermark information constitute the first target watermark information; The second target area image acquisition module 830 may be used to perform inverse wavelet transform processing on each of the modulation coefficient sets to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; The target watermark image generating module 840 may be used to update a plurality of the first target region images into corresponding second target region images in the target image, so as to generate a target watermark image.

[0081] The specific implementation of the image processing device is basically the same as the specific implementation of the above-mentioned image processing method, and will not be repeated here.

[0082] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above image processing method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0083] See also Fig. 9 , Fig. 9 The hardware structure of an electronic device of another embodiment is illustrated. The electronic device 900 includes: The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the image processing method of the embodiment of this application; Input / output interface 903, used to implement information input and output; Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.); A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904); The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0084] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and the computer program implements the above-mentioned image processing method when executed by a processor.

[0085] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0086] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0087] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0088] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0090] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0091] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0092] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0093] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0096] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. An image processing method, characterized in that: Applied to the terminal, including the following steps: Performing centroid analysis on the image area of ​​the captured target image, and determining a plurality of first target area images in the target image; According to the pre-generated first target watermark information, wavelet quantization modulation processing is performed on the plurality of first target area images respectively to obtain a plurality of modulation coefficient sets of the first target area images, wherein each of the modulation coefficient sets is embedded with the first target sub-watermark information, and the plurality of embedded first target sub-watermark information constitute the first target watermark information; Performing inverse wavelet transform processing on each of the modulation coefficient sets respectively to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; In the target image, a plurality of the first target area images are updated to corresponding second target area images to generate a target watermark image.

2. The method according to claim 1, characterized in that The performing centroid analysis on the image area of ​​the captured target image and determining a plurality of first target area images in the target image includes: Performing a regional image pixel distribution state analysis on the target image with respect to a preset image size to obtain first pixel distribution state information of the target image; According to the first pixel distribution state information, a region image in a target state in the target image is determined as the first target region image, wherein the target state is a state in which the centroid of the region image remains unchanged before and after wavelet quantization modulation processing is performed.

3. The method according to claim 1, characterized in that The step of performing wavelet quantization modulation processing on the plurality of first target area images respectively according to the pre-generated first target watermark information to obtain a modulation coefficient set of the plurality of first target area images comprises: Determining a target embedding quantity of the first target area image; Performing information segmentation processing on the first target watermark information according to the target embedding quantity, to obtain the first target sub-watermark information corresponding to each of a plurality of first target area images; Generating quantization coefficients for the first target area images according to the first target sub-watermark information respectively corresponding to the plurality of first target area images, to obtain quantization coefficient sets respectively corresponding to the plurality of first target area images; For each of the first target area images, based on the first target sub-watermark information corresponding to the first target area image and the corresponding quantization coefficient set, the first target area image is subjected to wavelet quantization modulation processing to obtain the corresponding modulation coefficient set.

4. The method according to claim 3, characterized in that The step of performing segmentation processing on the first target watermark information according to the target embedding quantity to obtain the first target sub-watermark information corresponding to each of the plurality of first target area images includes: Performing information segmentation processing on the first target watermark information according to the target embedding quantity to obtain a plurality of first target sub-watermark information; For each first target area image, the centroid of the first target area image is determined, and an association relationship is established between the centroid of the first target area image and one of the plurality of first target sub-watermark information.

5. An image processing method, characterized in that: Applied to the server, including the following steps: Get the target watermark image; Performing centroid analysis on the target watermark image for the image area to obtain a plurality of second target area images; Performing wavelet transform processing on the plurality of second target area images respectively to obtain a modulation coefficient set of the plurality of second target area images; Performing inverse wavelet quantization modulation processing on the modulation coefficient sets of the plurality of second target area images respectively to obtain second target sub-watermark information embedded in the plurality of modulation coefficient sets, and synthesizing the plurality of second target sub-watermark information to obtain second target watermark information in the target watermark image; The first target watermark information is obtained, and the second target watermark information is compared with the first target watermark information. When the second target watermark information is the same as the first target watermark information, it is determined that the target image corresponding to the target watermark image is the original image.

6. The method according to claim 5, characterized in that The step of performing centroid analysis on the target watermark image for the image area to obtain a plurality of second target area images includes: Performing a pixel distribution state analysis of a region image of a preset image size on the target watermark image to obtain second pixel distribution state information of the target watermark image; According to the second pixel distribution state information, a region image in a target state in the target watermark image is determined as the second target region image, wherein the target state is a state in which the region image performs wavelet quantization modulation processing and the centroid remains unchanged.

7. The method according to claim 5, characterized in that The method of performing inverse wavelet quantization modulation processing on the modulation coefficient sets of the plurality of second target area images to obtain second target sub-watermark information embedded in the plurality of modulation coefficient sets, and synthesizing the plurality of second target sub-watermark information to obtain the second target watermark information in the target watermark image comprises: Acquire a plurality of quantization coefficient sets corresponding to the second target area images respectively; For each second target area image, determining corresponding second target sub-watermark information from the modulation coefficient set of the second target area image by using the quantization coefficient set corresponding to the second target area image; The plurality of second target sub-watermark information are integrated to obtain the second target watermark information.

8. An image processing device, characterized in that: include: A first target area image acquisition module, configured to perform centroid analysis on the captured target image for the image area, and determine a plurality of first target area images in the target image; a watermark embedding module, configured to perform wavelet quantization modulation processing on a plurality of first target area images respectively according to pre-generated first target watermark information, so as to obtain a plurality of modulation coefficient sets of the first target area images, wherein each of the modulation coefficient sets is embedded with first target sub-watermark information, and a plurality of embedded first target sub-watermark information constitute the first target watermark information; A second target area image acquisition module, configured to perform inverse wavelet transform processing on each of the modulation coefficient sets to obtain a plurality of second target area images corresponding to the first target area images, wherein the centroid of the first target area image is consistent with the centroid of the corresponding second target area image; The target watermark image generating module is used to update the plurality of the first target area images into the corresponding second target area images in the target image, so as to generate a target watermark image.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the image processing method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the image processing method according to any one of claims 1 to 7 is implemented.

Images