CN111986089A - Image storage and comparison method, device, equipment and medium with characteristic value being integer - Google Patents

Abstract

The present application provides an image storage and comparison method, device, device and medium with integer eigenvalues, by scaling the acquired original image into a standard image of x×y pixel size, and dividing it into N pixel blocks; wherein , each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; let the three (x×y)/N-dimensional vectors in each pixel block be dimension-reduced and reorganized into integers , to obtain a set of 3N integers corresponding to the standard image; the set is used as the data storage form of the standard image to be stored in an image database that follows the data storage form, so as to check whether there are similar Pixel block or image. The present application converts the feature values of the pictures into integer form for easy storage and comparison, which greatly saves the comparison processing speed and the memory required for storage.

Description

Method, apparatus, device and medium for image storage and comparison with eigenvalue integerization

technical field

The present invention relates to the technical field of image processing, and in particular, to a method, device, device and medium for image storage and comparison with integer eigenvalues.

Background technique

At present, more and more scenes require the comparison of pictures, such as the common identification of embezzled or plagiarized patterns. As the plagiarism of pictures or patterns becomes more and more concealed, it is often necessary to locally compare the colors and shapes of the patterns in the pictures.

In the traditional image comparison process, it is necessary to compare the images to be compared with the images in the database one by one. There are also a lot of them, which results in a lot of comparison speed. The comparison speed is very slow, and local or subtle plagiarism patterns are often not found. In addition, the image data stored in the image database is also very large.

SUMMARY OF THE INVENTION

In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide an image storage and comparison method, apparatus, device and medium with integer eigenvalues, so as to solve at least one problem existing in the prior art.

In order to achieve the above purpose and other related purposes, the present application provides a method for storing and comparing images with integer eigenvalues. N pixel blocks; wherein, each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; let the three (x×y)/N-dimensional vectors in each pixel block be respectively Dimensionality reduction and reorganization into integers to obtain a set of 3N integers corresponding to the standard image; the set is used as the data storage form of the standard image to be stored in an image database that follows the data storage form, for use by integer ratios Check if there are similar pixel blocks or images.

In an embodiment of the present application, scaling the acquired original image into a standard image of x×y pixel size and dividing it into N pixel blocks includes: pruning four RGBA channels of the original image into three RGB channels , and scaled to a standard image of x×y pixel size; the standard image is divided according to N grids to obtain N pixel blocks.

In an embodiment of the present application, the scaling process removes the distortion of the original image by calculating the mean value of each channel in the pixel block.

In an embodiment of the present application, the three (x×y)/N-dimensional vectors in each pixel block are reduced in dimension and reorganized into integers respectively, so as to obtain a set of 3N integers corresponding to the standard image , including: converting the pixel value of each dimension in each of the vectors into 8-bit binary numbers to obtain an 8×(x×y)/N binary number matrix corresponding to each vector; The arrangement from the low order to the high order is rearranged and combined to form an integer for dimension reduction; the integers corresponding to all the pixel blocks of the standard image are collected to obtain a set of 3N integers corresponding to the standard image.

In an embodiment of the present application, the reorganization of the binary number matrix into an integer by reducing the dimension according to the arrangement of the low order to the high order includes: in the binary number matrix, each row corresponds to an 8-bit binary number of each dimension. number, and the bits of each dimension correspond from low to high from left to right; each column corresponds to the binary numbers that belong to the same bit in each dimension; the binary numbers that belong to the same bit in each dimension are combined into the corresponding bit According to the corresponding bits, the numerical segments are arranged in order from low to high, so as to recombine to obtain an integer corresponding to a vector including 8 numerical segments.

In an embodiment of the present application, determining whether there are similar pixel blocks or images by an integer comparison includes: setting a comparison line for an integer including 8 value segments, so that the integer is in the The value of one or more high-order value segments on the right side of the comparison line is compared with the value of one or more high-order value segments corresponding to each integer in the image database; if the comparison is the same, it is determined that the integer is similar ; If the comparison of at least 2 integers in the 3 integers corresponding to the pixel block is the same, then it is determined that there is a pixel block similar to the pixel block in the image database; if the 3N integers corresponding to the standard image exist If the comparison of at least m integers is the same, it is determined that there is an image similar to the standard image in the image database.

In an embodiment of the present application, the comparison line can be adjusted according to the comparison situation or scene requirements, so as to adjust the comparison accuracy.

In order to achieve the above purpose and other related purposes, the present application provides an image storage and comparison device with integer eigenvalues. The device includes: the device includes: a scaling and segmentation module for scaling the acquired original image to x A standard image of ×y pixel size is divided into N pixel blocks; each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; the integer conversion module is used to make each The three (x×y)/N-dimensional vectors in the pixel blocks are respectively dimensionally reduced and reorganized into integers to obtain a set of 3N integers corresponding to the standard image; the storage comparison module is used to use the set as the The data storage form of the standard image is stored in an image database conforming to the data storage form, so as to check whether there are similar pixel blocks or images through integer comparison.

In order to achieve the above purpose and other related purposes, the present application provides a computer device, the device includes: a memory and a processor; the memory is used to store computer instructions; the processor executes the computer instructions to implement the above method. .

In order to achieve the above object and other related objects, the present application provides a computer-readable storage medium storing computer instructions, and when the computer instructions are executed, the above-mentioned method is executed.

To sum up, a method, device, device and medium for image storage and comparison with integer eigenvalues provided by the present application, by scaling the acquired original image into a standard image of x×y pixel size, and dividing it into N pixel blocks; wherein, each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; let the three (x×y)/N-dimensional vectors in each pixel block decrease respectively The dimensions are merged into integers to obtain a set of 3N integers corresponding to the standard image; the set is used as the data storage form of the standard image to be stored in an image database that follows the data storage form for comparison by integers Check if there are similar pixel blocks or images.

Has the following beneficial effects:

The present application converts the feature values of the pictures into integer form for easy storage and comparison, which greatly saves the comparison processing speed and the memory required for storage.

Description of drawings

FIG. 1 is a schematic flowchart of an image storage and comparison method for eigenvalue integerization in an embodiment of the present application.

FIG. 2 is a schematic diagram of a scene corresponding to step S101 in an embodiment of the present application.

FIG. 3 is a schematic block diagram of an image storage and comparison apparatus for eigenvalue integerization according to an embodiment of the present application.

FIG. 4 is a schematic structural diagram of a computer device in an embodiment of the present application.

Detailed ways

The embodiments of the present application are described below through specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other under the condition of no conflict.

It should be noted that the drawings provided in the following embodiments are only used to illustrate the basic concept of the present application in a schematic way, although the drawings only show the components related to the present application rather than the number, shape and number of components in actual implementation. The dimensions are drawn, but the type, quantity and proportion of each component can be arbitrarily changed in actual implementation, and the component layout may also be more complicated.

Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case of "direct connection" but also the case of "indirect connection" with other elements interposed therebetween. In addition, when it says that a certain part "includes" a certain constituent element, unless there is particularly no description to the contrary, it does not exclude other constituent elements, but means that other constituent elements may also be included.

The terms first, second, and third mentioned herein are used for the purpose of describing various parts, components, regions, layers and/or sections and are not intended to be limiting. These terms are only used to distinguish one part, component, region, layer or section from another part, component, region, layer or section. Thus, recitation of a first part, component, region, layer or section below may refer to a second part, component, region, layer or section without departing from the scope of the present application.

Also, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context dictates otherwise. It should be further understood that the terms "comprising", "comprising" indicate the presence of a stated feature, operation, element, component, item, kind, and/or group, but do not exclude one or more other features, operations, elements, components, The existence, appearance or addition of items, categories, and/or groups. The terms "or" and "and/or" as used herein are to be construed to be inclusive or to mean any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C" . Exceptions to this definition arise only when combinations of elements, functions, or operations are inherently mutually exclusive in some way.

In the traditional image comparison process, it is necessary to compare the images to be compared with the images in the database one by one. For example, the common feature vector extracted from the image is compared, but the feature vector or pixel memory contained in a There are a lot of them, which results in a lot of comparison speeds. The comparison speed is very slow, and local or subtle plagiarism patterns are often not found. In addition, the data storage of pictures in the picture database is also very large.

In order to solve the above problems, the present application proposes a method, device, equipment and medium for image storage and comparison with integer eigenvalues, which converts the eigenvalues of pictures into integer form, which is convenient for storage and comparison, and greatly saves the comparison speed. and memory required for storage.

As shown in FIG. 1 , a schematic flowchart of an image storage and comparison method for eigenvalue integerization in an embodiment of the present application is shown. As shown, the method includes:

Step S101: Scale the acquired original image into a standard image of x×y pixel size, and divide it into N pixel blocks; wherein each pixel block has three (x×y)/N dimensions corresponding to three RGB channels respectively. vector.

In an embodiment of the present application, scaling the acquired original image into a standard image with a size of x×y pixels and dividing it into N pixel blocks includes:

A. Reduce the RGBA four channels of the original image to RGB three channels, and scale it to a standard image of x×y pixel size;

In this embodiment, an original image usually has four RGBA channels, which represent the color spaces of Red (red), Green (green), Blue (blue) and Alpha respectively, but it is only an addition to the RGB model. additional information. The color used is usually RGB, and the Alpha channel is generally used as an opacity parameter. Therefore, this application removes the Alpha channel that has little or no impact in the image comparison process to reduce the number of channels, thereby reducing the comparison. data used.

In addition, the pixel size of an original image is usually different, and often has a larger pixel size, such as 4032×3024, 2048×1024, etc. In order to facilitate this application, the image is converted into an integer and subsequently stored for comparison. , the present application uniformly scales the original image to a smaller or extremely small uniform pixel size, such as a pixel size of 12×12, to be unified as a standard image, as shown in FIG. 2 . The zooming method in the present application may use some common zooming methods in the field of image processing technology.

In this embodiment, since the image scaling process will bring about the problem of image distortion, the present application eliminates the distortion of the original image by calculating the mean value of each channel in the pixel block in the scaling process. For example, weights are assigned to each pixel, and normalization is performed to eliminate distortion by numerical difference method.

It should be noted that, the process of eliminating distortion in this method may also adopt a common method of dealing with image distortion. In addition, the effect of processing image distortion here does not require extremely high standards, because the purpose of performing a series of processing around images in this application is to compare pictures, such as comparing the color or shape of patterns in a certain area, It is not for use or appreciation, etc., as long as there is no major change in the feature information corresponding to the pattern in this area, the impact on the picture comparison is small. Therefore, the requirements for image distortion processing are not too high.

B. The standard image is divided according to N grids to obtain N pixel blocks.

具体向量如下：For example, as shown in FIG. 2, which is shown as a schematic diagram of a scene from an original image to a pixel block. After the original image is scaled to a standard image with a pixel size of 12×12, it is divided according to the nine-square grid frame, and nine pixel blocks with a pixel size of 4×4 can be obtained. Correspondingly, each pixel block has three 16-dimensional ((12×12)/9=4×4) vectors corresponding to the three RGB channels:

The specific vector is as follows:

It should be noted that the N-grid for dividing the standard image in this application is not limited to the centrally symmetric four-grid, nine-grid, sixteen-grid, etc., but also includes, for example, six-grid, eight-grid, twelve-grid, etc. Non-centrosymmetric multi-grid. In addition, each pixel block divided by N grids is preferably a square or a rectangle.

Step S102 : reducing the dimensions of the three (x×y)/N-dimensional vectors in each pixel block and reorganizing them into integers to obtain a set of 3N integers corresponding to the standard image.

In an embodiment of the present application, the three (x×y)/N-dimensional vectors in each pixel block are respectively reduced in dimension and reorganized into integers, so as to obtain a set of 3N integers corresponding to the standard image, include:

A. Convert the pixel value of each dimension in each of the vectors into 8-bit binary numbers to obtain an 8×(x×y)/N binary number matrix corresponding to each vector.

的第一个维度R₁的像素值对应转为8为二进制数如下所示：For example, the vector

The pixel value of ₁ in the first dimension R corresponds to 8 converted to a binary number as follows:

R ₁ ={r ₁₁ ,r ₁₂ ,...,r ₁₈ };

It should be noted that the range of pixel values in each channel of the three RGB channels is (0 to 255), and the corresponding binary value is exactly 8 bits (00000000 to 11111111). Therefore, the pixel value of each dimension can be converted into 8 Bit binary number.

所得到的二进制数矩阵如下所示；Further, it is assumed that each vector as exemplified in Figure 2 is 16-dimensional, then if the vector

The resulting matrix of binary numbers is shown below;

Specifically, in the binary number matrix formula (1) exemplified above, each row corresponds to an 8-bit binary number of each dimension, and the bits of each dimension correspond from left to right in order from low to high, such as the first In the row, r ₁₁ corresponds to the lowest bit, and r ₁₈ corresponds to the highest bit; each column corresponds to the binary numbers belonging to the same (high and low) bits in each dimension, such as r ₁₁ , r ₂₁ , ..., r ₁₆₁ in the first column It corresponds to the binary numbers that belong to the same low-order bit in each dimension.

B. Rearrange and combine the binary number matrix according to the arrangement from the low order to the high order, so as to reduce the dimension and reorganize it into an integer. Specifically include:

b1. Combine the binary numbers belonging to the same bit in each dimension into a numerical segment corresponding to the bit;

的二进制数矩阵公式(1)中，得到对应向量

的整数如下所示：When converting a matrix to a row of integers, it may be naturally arranged in horizontal numbering order, which is also common practice. However, the innovative proposal of the present application is arranged in vertical combination according to the same position. vector as above

In the binary matrix formula (1) of , the corresponding vector is obtained

The integers are as follows:

{r ₁₁ ,r ₂₁ ,…,r ₁₆₁ |r ₁₂ ,r ₂₂ ,…,r ₁₆₂ |…|r ₁₈ ,r ₂₈ ,…,r ₁₆₈ }; (2)

b2. According to each of the numerical segments, the corresponding bits are arranged in order from the low order to the high order, so as to recombine to obtain an integer corresponding to a vector including 8 numerical segments.

的整数如上所举例的整数公式(2)，其中，该整数包含8个数值区段的整数。Correspondingly, in the integer formula (2) exemplified above, r ₁₁ to r ₁₆₁ correspond to the lowest value segment; r ₁₈ to r ₁₆₈ correspond to the highest value segment, in the order from low to high Arrange in order to get the corresponding vector

The integer of is the integer formula (2) exemplified above, wherein the integer includes an integer of 8 value segments.

C. Collect integers corresponding to all pixel blocks of the standard image to obtain a set of 3N integers corresponding to the standard image.

而如上举例可知，一个像素块中有3个向量，一个标准图像则又包含9个像素块，因此，一个标准图像则对应有27个整数的集合。For example, the integer formula (2) as exemplified above actually corresponds to only one vector in one pixel block

As can be seen from the above example, there are 3 vectors in a pixel block, and a standard image includes 9 pixel blocks. Therefore, a standard image corresponds to a set of 27 integers.

Step S103: Use the set as the data storage form of the standard image to store in an image database that follows the data storage form, so as to check whether there are similar pixel blocks or images through integer comparison.

It should be noted that extracting features from images and expressing them as integers for storage and comparison will greatly reduce the memory occupied and the calculation speed compared with directly storing images or feature vectors.

In this embodiment, the massive images stored in the image database are also in the storage form of integer sets. Therefore, similar images can be judged by comparing integers with integers.

In this embodiment of the present application, this step S103 specifically includes:

A. A comparison line is set for an integer including 8 value segments, so that the value of one or more high-order value segments on the right side of the comparison line in the integer corresponds to the number corresponding to each integer in the image database Compare the values of one or more high-value segments;

It should be emphasized that, further, in this application, the integers that characterize the image features have been converted. Since the binary matrix for the corresponding vector is arranged in the order from the low order to the high order, the integer and the high order of the integer can be directly carried out. compared to. Because, if the 32 high-order bits of the integer converted by the method described in this application are the same, then the high-order 2 bits of the 16-dimensional vector corresponding to this integer must be the same, and the low-order bits can be used as noises that allow users to add text and logos.

Therefore, according to the characteristics of arranging in the order of low order to high order, the present application sets up a comparison line for an integer including 8 numerical segments, and makes some integers to be compared, such as several numerical segments in the rear of the integer. right.

In addition, the comparison line can be adjusted according to the comparison situation or scene requirements, so as to adjust the comparison accuracy.

For example, the desired alignment accuracy can be achieved by setting the alignment line in the 2nd value field or the 3rd value block and then performing the alignment.

B. If the comparison is the same, it is determined that the integers are similar;

C. If at least two integers among the three integers corresponding to the pixel block are determined to be the same by comparison, it is determined that a pixel block similar to the pixel block exists in the image database.

D. If at least m integers among the 3N integers corresponding to the standard image are determined to be the same by comparison, it is determined that there is an image similar to the standard image in the image database.

For example, assuming that all 27 integers are the same, it can be determined as the same image; if one or more integers belonging to a pixel block are the same, it can also be determined that there are similar or identical pixel blocks in the pixel block. It should be noted that a pixel block represents a part of an image (such as one-ninth of the area), and there may be a complete pattern or partial pattern in this part, then for local or subtle patterns in the image, the ratio can also be realized. Yes, in order to judge whether the pattern in the image has the possibility of plagiarism or infringement.

In the actual application of this method, if there are more than 4 integers in the 27 integers that are similar, it can be judged as very similar or identical images, and images that are highly similar or identical to standard images in the image database can be found. Therefore, the present application judges similar or identical images through the comparison of integers, which greatly reduces the processing speed.

To sum up, a method, device, device and medium for image storage and comparison with eigenvalue integerization proposed in this application, by scaling the acquired original image into a standard image of x×y pixel size, and dividing it into N pixel blocks; wherein, each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; let the three (x×y)/N-dimensional vectors in each pixel block decrease respectively The dimensions are merged into integers to obtain a set of 3N integers corresponding to the standard image; the set is used as the data storage form of the standard image to be stored in an image database that follows the data storage form for comparison by integers Check if there are similar pixel blocks or images. The present application converts the feature values of the pictures into integer form for easy storage and comparison, which greatly saves the comparison processing speed and the memory required for storage.

As shown in FIG. 3 , it is a block diagram of an image storage and comparison apparatus for eigenvalue integerization according to an embodiment of the present application. As shown, the apparatus 300 includes:

The scaling and dividing module 301 is used to scale the obtained original image into a standard image of x×y pixel size, and divide it into N pixel blocks; wherein, each pixel block has three (x×y) corresponding RGB three channels respectively. )/N-dimensional vector;

Integer conversion module 302, for making three (x×y)/N-dimensional vectors in each pixel block to be dimension-reduced and reorganized into integers to obtain a set of 3N integers corresponding to the standard image;

The storage comparison module 303 is configured to use the set as a data storage form of the standard image to store in an image database conforming to the data storage form, so as to check whether there are similar pixel blocks or images through integer comparison.

It should be noted that the information exchange, execution process, etc. among the modules/units of the above-mentioned device are based on the same concept as the method embodiments described in the present application, and the technical effects brought by them are the same as those of the method embodiments of the present application. For the content, reference may be made to the descriptions in the method embodiments shown in the foregoing application, and details are not repeated here.

It should also be noted that it should be understood that the division of each module of the above apparatus is only a division of logical functions, and may be fully or partially integrated into a physical entity during actual implementation, or may be physically separated. And these units can all be implemented in the form of software calling through processing elements; they can also all be implemented in hardware; some modules can also be implemented in the form of calling software through processing elements, and some modules can be implemented in hardware. For example, the storage and comparison module 303 may be a separately established processing element, or may be integrated into a certain chip of the above-mentioned system to realize, in addition, it may also be stored in the memory of the above-mentioned system in the form of program code, and it can be stored by a certain of the above-mentioned device. A processing element invokes and executes the above functions of the storage comparison module 303 . The implementation of other modules is similar. In addition, all or part of these modules can be integrated together, and can also be implemented independently. The processing element described here may be an integrated circuit with signal processing capability. In the implementation process, each step of the above-mentioned method or each of the above-mentioned modules can be completed by an integrated logic circuit of hardware in the processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), or one or more microprocessors ( digital signal processor, referred to as DSP), or, one or more Field Programmable Gate Array (Field Programmable Gate Array, referred to as FPGA) and the like. For another example, when one of the above modules is implemented in the form of processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU for short) or other processors that can call program codes. For another example, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC for short).

As shown in FIG. 4 , a schematic structural diagram of a computer device in an embodiment of the present application is shown. As shown in the figure, the computer device 400 includes: a memory 401 and a processor 402; the memory 401 is used to store computer instructions; the processor 402 executes the computer instructions to implement the method described in FIG. 1 .

In some embodiments, the number of the memory 401 in the computer device 400 may be one or more, the number of the processor 402 may be one or more, and in FIG. example.

In an embodiment of the present application, the processor 402 in the computer device 400 loads one or more instructions corresponding to the process of the application program into the memory 401 according to the steps shown in FIG. The controller 402 is used to run the application program stored in the memory 401, thereby implementing the method described in FIG. 1 .

The memory 401 may include random access memory (Random Access Memory, RAM for short), and may also include non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 401 stores operating systems and operation instructions, executable modules or data structures, or their subsets, or their extended sets, wherein the operation instructions may include various operation instructions for implementing various operations. The operating system may include various system programs for implementing various basic services and handling hardware-based tasks.

The processor 402 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; it may also be a digital signal processor (Digital Signal Processing, DSP for short) ), Application Specific Integrated Circuit (ASIC for short), Field-Programmable Gate Array (FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

In some specific applications, various components of the computer device 400 are coupled together through a bus system, where the bus system may include a power bus, a control bus, a status signal bus, and the like in addition to a data bus. However, for the sake of clarity of illustration, the various buses are referred to as bus systems in FIG. 4 .

In an embodiment of the present application, the present application provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the method described in FIG. 1 .

At any possible level of incorporation of technical details, the present application may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the present application.

A computer-readable storage medium may be a tangible device that can hold and store instructions for use by the instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer readable storage media include: portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM) or flash memory), static random access memory (SRAM), portable compact disk read only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically coded devices, such as printers with instructions stored thereon Hole cards or raised structures in grooves, and any suitable combination of the above. Computer-readable storage media, as used herein, are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (eg, light pulses through fiber optic cables), or through electrical wires transmitted electrical signals.

The computer-readable programs described herein can be downloaded to various computing/processing devices from computer-readable storage media, or to external computers or external storage devices over a network, eg, the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from a network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .

Computer program instructions for carrying out the operations of the present application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or in one or more source or object code written in any combination of programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and procedural programming languages, such as the "C" language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server implement. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through the Internet connect). In some embodiments, custom electronic circuits, such as programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), can be personalized by utilizing state information of computer readable program instructions. Computer readable program instructions are executed to implement various aspects of the present application.

To sum up, a method, device, device and medium for image storage and comparison with integer eigenvalues provided by the present application, by scaling the acquired original image into a standard image of x×y pixel size, and dividing it into N pixel blocks; wherein, each pixel block has three (x×y)/N-dimensional vectors corresponding to the three RGB channels respectively; let the three (x×y)/N-dimensional vectors in each pixel block decrease respectively The dimensions are merged into integers to obtain a set of 3N integers corresponding to the standard image; the set is used as the data storage form of the standard image to be stored in an image database that follows the data storage form for comparison by integers Check if there are similar pixel blocks or images.

The present application effectively overcomes various shortcomings in the prior art and has high industrial application value.

The above-mentioned embodiments merely illustrate the principles and effects of the present application, but are not intended to limit the present invention. Anyone skilled in the art can make modifications or changes to the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical idea disclosed in the present invention should still be covered by the claims of the present application.

Claims (10)

1. an image storage and comparison method of eigenvalue integerization, is characterized in that, described method comprises: The obtained original image is scaled to a standard image of x×y pixel size, and divided into N pixel blocks; wherein, each pixel block has three (x×y)/N-dimensional vectors corresponding to three RGB channels respectively; Let the three (x×y)/N-dimensional vectors in each pixel block be dimension-reduced and reorganized into integers to obtain a set of 3N integers corresponding to the standard image; The set is used as the data storage form of the standard image to be stored in an image database conforming to the data storage form, so as to check whether there are similar pixel blocks or images through integer comparison. 2. The method according to claim 1, characterized in that, scaling the acquired original image to a standard image of x×y pixel size and dividing it into N pixel blocks, comprising: Reduce the RGBA four-channel of the original image to RGB three-channel, and scale it to a standard image of x×y pixel size; The standard image is divided into N grids to obtain N pixel blocks. 3. The method according to claim 2, wherein the scaling process eliminates the distortion of the original image by calculating the mean value of each channel in the pixel block. 4 . The method according to claim 1 , wherein the three (x×y)/N-dimensional vectors in each pixel block are dimension-reduced and reorganized into integers to obtain the corresponding standard image. 5 . A set of 3N integers, including: Converting the pixel value of each dimension in each of the vectors into 8-bit binary numbers to obtain a 8×(x×y)/N binary number matrix corresponding to each vector; Rearranging and combining the binary number matrix according to the arrangement of the low order to the high order, and reorganizing it into an integer in order to reduce the dimension; The integers corresponding to all pixel blocks of the standard image are collected to obtain a set of 3N integers corresponding to the standard image. 5. The method according to claim 4, wherein the binary number matrix is reorganized into an integer according to the arrangement of low order to high order with dimension reduction, comprising: In the binary number matrix, each row corresponds to an 8-bit binary number of each dimension, and the bits of each dimension correspond from left to right in order from low to high; each column corresponds to the binary numbers belonging to the same bit in each dimension. ; Combine binary numbers that belong to the same bit in each dimension into a numerical segment corresponding to that bit; According to the corresponding bits, the numerical segments are arranged in order from low to high, so as to recombine to obtain an integer corresponding to a vector including 8 numerical segments. 6. The method according to claim 5, characterized in that, determining whether there are similar pixel blocks or images through integer comparison, comprising: An alignment line is set for an integer including 8 value segments, so that the value of one or more high-order numeric segments to the right of the alignment line in the integer is one or more corresponding to each integer in the image database. Compare the values of multiple high-value segments; If the comparisons are identical, the integers are determined to be similar; If the comparison of at least 2 integers among the 3 integers corresponding to the pixel block is determined to be the same, then it is determined that a pixel block similar to the pixel block exists in the image database; If at least m integers among the 3N integers corresponding to the standard image are determined to be the same by comparison, it is determined that an image similar to the standard image exists in the image database. 7 . The method according to claim 6 , wherein the comparison line can be adjusted according to the comparison situation or scene requirements, so as to adjust the comparison accuracy. 8 . 8. A device for storing and comparing images with integer eigenvalues, wherein the device comprises: The scaling and segmentation module is used to scale the obtained original image into a standard image of x×y pixel size, and divide it into N pixel blocks; each pixel block has three (x×y) corresponding RGB three channels respectively. /N-dimensional vector; Integer conversion module, for making three (x×y)/N-dimensional vectors in each pixel block to be reduced in dimension and reorganized into integers respectively, so as to obtain a set of 3N integers corresponding to the standard image; The storage and comparison module is used for using the set as the data storage form of the standard image to store in the image database conforming to the data storage form, so as to check whether there are similar pixel blocks or images through integer comparison. 9. A computer device, characterized in that, the device comprises: a memory and a processor; the memory is used to store computer instructions; the processor executes the computer instructions to implement any one of claims 1 to 7. method described. 10. A computer-readable storage medium, characterized by storing computer instructions that, when executed, perform the method of any one of claims 1 to 7.

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