CN117095186B - Color card identification method and device, electronic equipment and storage medium - Google Patents

Abstract

The disclosure relates to a color card identification method and device, an electronic device and a storage medium, wherein the method comprises the following steps: performing color lump recognition on the color lump image to obtain a recognized color lump, wherein the color lump image comprises two color lump areas in the same color lump tool; determining a first color block and a second color block in the color blocks according to the coordinates of the color blocks, wherein the distance between the first color block and the second color block meets a distance condition; clustering all color blocks by taking the first color block and the second color block as clustering center points respectively to obtain a first class color block and a second class color block; the first class color block and the second class color block are divided into two areas. The embodiment of the disclosure can be convenient for rapidly and accurately distinguishing the color blocks of the two areas, and realizes the accurate division of the areas to which the color blocks belong.

Description

Color card identification method and device, electronic device and storage medium

Technical Field

The present disclosure relates to the field of computer technology, and in particular to a color card recognition method, device, electronic device and storage medium.

Background technique

Image signal processing (ISP) algorithms can extract high-quality digital images from raw data captured by image sensors (such as CMOS or CCD). Clear and accurate images are obtained by denoising, enhancing, and optimizing the raw data. ISP algorithms are widely used in various application scenarios related to image acquisition, such as smartphones, cameras, security monitoring, medical image processing, and autonomous driving.

The Color Correction Matrix (CCM) is a very important module in the ISP processing flow. Since the image sensor's response to the three primary colors is quite different from that of the human eye, and there is crosstalk between pixels, the image data output by the image sensor can only be restored to the true color that conforms to human eye perception after passing through the CCM module.

In the process of color correction through the CCM module, it is necessary to calculate the CCM value through a color card. A color card is a pre-set card including multiple color blocks. Each color block has a preset color. The colors of the color blocks are different. Multiple color blocks (commonly used are 24 color blocks) are used to cover a wide color range as much as possible. It is used for color selection, comparison, and communication to achieve the unification of color standards within a certain range.

In this process, an image sensor is usually used to capture a color card. However, for some color cards with more functions, there are often multiple different color card areas to achieve different color correction functions. If a certain correction only needs to use one of the color card areas, the different color card areas need to be distinguished. However, the existing color card area recognition method has a low accuracy rate.

Summary of the invention

The present disclosure proposes a color card recognition technology solution.

According to one aspect of the present disclosure, a color card recognition method is provided, comprising:

Performing color block recognition on the color card image to obtain recognized color blocks, wherein the color card image includes two color card areas in the same color card tool;

Determine, according to the coordinates of the color blocks, a first color block and a second color block in the color blocks, wherein a distance between the first color block and the second color block satisfies a distance condition;

Taking the first color block and the second color block as cluster center points respectively, clustering all color blocks to obtain first category color blocks and second category color blocks;

The first category color blocks and the second category color blocks are divided into two areas.

In a possible implementation, determining the first color block and the second color block in the color blocks according to the coordinates of the color blocks includes:

According to the coordinates of the color block, two color blocks with the farthest distance from each other among all the color blocks are determined as the first color block and the second color block.

In a possible implementation, determining the first color block and the second color block in the color blocks according to the coordinates of the color blocks includes:

According to the ordinate of the center point of the color block, the color blocks with the minimum and maximum ordinate values are determined respectively;

Based on the minimum and maximum values of the ordinate, determine the top row of color blocks and the bottom row of color blocks;

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, determining the top row of color blocks and the bottom row of color blocks based on the minimum and maximum values of the ordinates includes:

Based on the minimum value of the ordinate, determine the color blocks whose ordinate values are within a first range as the color blocks in the top row, wherein the first range includes: the minimum value of the ordinate minus half the size of the color block to the minimum value of the ordinate plus half the size of the color block;

Based on the maximum ordinate value, determine the color blocks whose ordinate values are within a second range as the color blocks in the bottom row, where the second range includes: the maximum ordinate value minus half the color block size to the maximum ordinate value plus half the color block size.

In a possible implementation, selecting a color block in the top row of color blocks as the first color block and selecting a color block in the bottom row of color blocks as the second color block based on the horizontal coordinate of the center point of the color block includes:

The color block with the smallest horizontal coordinate in the top row of color blocks is used as the first color block, and the color block with the largest horizontal coordinate in the bottom row of color blocks is used as the first color block; or,

The color block with the largest horizontal coordinate in the top row of color blocks is taken as the first color block, and the color block with the smallest horizontal coordinate in the bottom row of color blocks is taken as the first color block; or,

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, clustering all the color blocks using the first color block and the second color block as cluster centers to obtain first category color blocks and second category color blocks includes:

The first color block and the second color block are used as cluster center points, and based on the position of each color block, all color blocks are clustered to obtain first category color blocks and second category color blocks.

In a possible implementation, clustering all the color blocks using the first color block and the second color block as cluster centers to obtain first category color blocks and second category color blocks includes:

For all color blocks, calculate the distance between each color block and the two cluster center points;

Classify each color block into the class corresponding to the cluster center point with the smallest distance, and obtain the first category color block and the second category color block;

According to the positions of the first category color blocks and the second category color blocks, respectively determine the centroids of the first category color blocks and the second category color blocks as new clustering center points of the first category color blocks and the second category color blocks;

The above process of calculating the distance to determine the new cluster center point is iteratively performed until the iteration stop condition is met, and the reclassified first category color blocks and second category color blocks are obtained.

According to one aspect of the present disclosure, there is provided a color card recognition device, comprising:

A color block recognition module is used to perform color block recognition on a color card image to obtain recognized color blocks, wherein the color card image includes two color card areas in the same color card tool;

A center point determination module, used to determine a first color block and a second color block in the color blocks according to the coordinates of the color blocks, wherein the distance between the first color block and the second color block satisfies a distance condition;

A clustering module, configured to cluster all the color blocks using the first color block and the second color block as cluster centers respectively, to obtain first category color blocks and second category color blocks;

The area division module is used to divide the first category color blocks and the second category color blocks into two areas.

In a possible implementation, the center point determination module is used to:

According to the coordinates of the color block, two color blocks with the farthest distance from each other among all the color blocks are determined as the first color block and the second color block.

In a possible implementation, the center point determination module is used to:

According to the ordinate of the center point of the color block, the color blocks with the minimum and maximum ordinate values are determined respectively;

Based on the minimum and maximum values of the ordinate, determine the top row of color blocks and the bottom row of color blocks;

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, the center point determination module is used to:

Based on the minimum value of the ordinate, determine the color blocks whose ordinate values are within a first range as the color blocks in the top row, wherein the first range includes: the minimum value of the ordinate minus half the size of the color block to the minimum value of the ordinate plus half the size of the color block;

Based on the maximum ordinate value, determine the color blocks whose ordinate values are within a second range as the color blocks in the bottom row, where the second range includes: the maximum ordinate value minus half the color block size to the maximum ordinate value plus half the color block size.

In a possible implementation, the center point determination module is used to:

The color block with the smallest horizontal coordinate in the top row of color blocks is used as the first color block, and the color block with the largest horizontal coordinate in the bottom row of color blocks is used as the first color block; or,

The color block with the largest horizontal coordinate in the top row of color blocks is taken as the first color block, and the color block with the smallest horizontal coordinate in the bottom row of color blocks is taken as the first color block; or,

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, the clustering module is used to:

The first color block and the second color block are used as cluster center points, and based on the position of each color block, all color blocks are clustered to obtain first category color blocks and second category color blocks.

In a possible implementation, the clustering module is used to:

For all color blocks, calculate the distance between each color block and the two cluster center points;

Classify each color block into the class corresponding to the cluster center point with the smallest distance, and obtain the first category color block and the second category color block;

According to the positions of the first category color blocks and the second category color blocks, respectively determine the centroids of the first category color blocks and the second category color blocks as new clustering center points of the first category color blocks and the second category color blocks;

The above process of calculating the distance to determine the new cluster center point is iteratively performed until the iteration stop condition is met, and the reclassified first category color blocks and second category color blocks are obtained.

According to one aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to call the instructions stored in the memory to execute the above method.

According to one aspect of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor.

In the disclosed embodiment, color block recognition is performed on the color card image to obtain the recognized color blocks, and then the first color block and the second color block in the color blocks are determined according to the coordinates of the color blocks, and the distance between the first color block and the second color block meets the distance condition; the first color block and the second color block are respectively used as cluster center points to cluster all the color blocks to obtain the first category color blocks and the second category color blocks; the first category color blocks and the second category color blocks are divided into two areas. Therefore, by selecting the first color block and the second color block that meet the distance condition as the cluster center points, clustering all the color blocks, it is possible to quickly and accurately distinguish the color blocks in the two areas, and realize accurate division of the areas to which the color blocks belong.

It should be understood that the above general description and the following detailed description are exemplary and explanatory only and do not limit the present disclosure. Other features and aspects of the present disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

FIG. 1 is a schematic diagram showing a color chart image output by an image sensor before and after CCM correction.

FIG. 2 is a schematic diagram showing a color card image of a multifunctional color card including upper and lower areas.

FIG. 3 shows a flow chart of a color card recognition method according to an embodiment of the present disclosure.

FIG. 4 shows a block diagram of a color card recognition device according to an embodiment of the present disclosure.

FIG5 shows a block diagram of an electronic device according to an embodiment of the present disclosure.

Detailed ways

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

The term "and/or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and/or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

The function of CCM image correction is to correct the spectral response of the image sensor. After correction, the image is more consistent with the real color perceived by the human eye. Figure 1 shows a schematic diagram of the color card image output by the image sensor before and after CCM correction. Among them, the image in part (a) of Figure 1 is the color card image output before CCM correction, and the image in part (b) of Figure 1 is the color card image output after CCM correction.

CCM is a 3×3 matrix. When calculating the CCM matrix value of an image sensor, the image sensor is usually used to shoot a color card, and then the R, G, B average values of each color block in the color card image are polynomially fitted with the R, G, B target values of each color block in the X-Rite standard to obtain the optimized CCM matrix coefficients.

Current color cards often have many functions. As an example, FIG2 shows a schematic diagram of a color card image of a multifunctional color card including upper and lower areas. In this figure, in addition to the conventional 24 color blocks in the lower half, there are also creative enhancement color blocks in the upper half, which are used to add novel color effects to videos and images, such as creative warm and cold tones. Through this color card, color correction and creative enhancement tasks can be completed, which is very helpful for video production and post-processing editing efficiency.

After all color blocks are automatically identified in the image, how to automatically distinguish the upper and lower color blocks and only adjust the CCM value of the lower or upper color blocks is a common engineering problem.

In the related art, to distinguish between the upper and lower color blocks, a threshold value Ty is usually pre-set in the Y direction of the image coordinate system (the upper left corner of the image is the origin). When the y coordinate value of the center point of a color block is less than Ty, it belongs to the upper half; conversely, if the y coordinate value of the center point of a color block is greater than Ty, it belongs to the lower half. However, since the position of the color card in the image always changes every time the image is taken, the artificially set Ty may not conform to the actual situation, thereby incorrectly judging whether the current color block is in the upper half or the lower half, and the accuracy is low.

The present disclosure provides a color card recognition method. In the embodiment of the present disclosure, color block recognition is performed on a color card image. After the recognized color blocks are obtained, the first color block and the second color block in the color blocks are determined according to the coordinates of the color blocks, and the distance between the first color block and the second color block meets the distance condition; the first color block and the second color block are respectively used as cluster center points to cluster all the color blocks to obtain the first category color blocks and the second category color blocks; the first category color blocks and the second category color blocks are divided into two areas. Therefore, by selecting the first color block and the second color block that meet the distance condition as the cluster center points, clustering all the color blocks, it is possible to quickly and accurately distinguish the color blocks in the two areas, and realize accurate division of the areas to which the color blocks belong.

FIG3 shows a flow chart of a color card recognition method according to an embodiment of the present disclosure. As shown in FIG3 , the method includes:

In step S11, color block recognition is performed on the color card image to obtain recognized color blocks, wherein the color card image includes two color card areas in the same color card tool;

The color card image is an image of the color card captured by the image sensor. In the present disclosure, the color card image may include two color card areas. For example, in the image shown in FIG2 , the color card includes an upper and lower area. The lower area includes 24 color blocks, and the upper area includes 26 color blocks. The two color blocks correspond to different color calibration functions. In order to facilitate subsequent color block recognition, when the color card is photographed by the image sensor, the image sensor may be directed to the color card to avoid a large difference between the relative position of the color blocks in the image and the actual relative position of the color blocks due to the perspective effect of near being larger and far being smaller, so as to facilitate the subsequent accurate distinction of the two color card areas based on the position of the color blocks in the image.

In this step, the recognition of color blocks can be to completely recognize all color blocks in the color card image, so as to facilitate the subsequent division of the area to which the color blocks belong based on the positions of the color blocks. There can be many specific recognition methods. In one example, the recognition can be based on an automatic or semi-automatic method. For example, after the partial color blocks are initially recognized by the algorithm, the remaining color blocks are identified with the help of manual annotation. In another example, all color blocks can be recognized based on a fully automatic recognition method. In one example, the color blocks can be recognized by threshold segmentation based on the difference between the pixel value of the color block and the background pixel value; in another example, the color blocks can also be recognized by edge detection-based segmentation based on the change of the gray value of the edge of the color block; in another example, the color blocks can also be recognized by encoding the image features based on a deep learning algorithm and using a neural network. The neural network can be, for example, a convolutional neural network, a residual neural network, and the like.

In step S12, a first color block and a second color block in the color blocks are determined according to the coordinates of the color blocks, and the distance between the first color block and the second color block satisfies a distance condition;

Here, the coordinates of the color block are the coordinates of the color block in the image coordinate system, and specifically may be the coordinates of the center point of the color block, or may also be the coordinates of a corner point of the color block, which is not specifically limited in the present disclosure.

The distance between the first color block and the second color block is the distance between the first color block and the second color block on the image. It should be noted that in the embodiment of the present disclosure, it is not necessary to calculate the distance between the first color block and the second color block. Instead, the distance between the color blocks can be determined based on the coordinate values of the color blocks. For example, based on the y value of the color block, it can be determined whether the color block belongs to the top row or the bottom row, and then based on the x value of the color block, the position of the color block in the color card can be determined, that is, the distance between the color blocks is determined. For details, please refer to the possible implementation methods provided in the present disclosure, which will not be elaborated here.

There may be multiple distance conditions here. In one possible implementation, the distance condition may be the two color blocks that are the farthest apart from each other among all color blocks. In another possible implementation, when the positional relationship of the two color card areas is an up-and-down adjacent relationship, the distance condition may be the farthest vertical distance among all color blocks. In another possible implementation, when the positional relationship of the two color card areas is a left-and-right adjacent relationship, the distance condition may be the farthest horizontal distance among all color blocks. In another possible implementation, the distance condition may be the farthest vertical distance and the farthest horizontal distance among all color blocks.

The distances of color blocks can be compared based on the coordinates of the color blocks. For example, the distances of different color blocks can be determined based on the comparison of the size of the x coordinate and the size of the y coordinate. In addition, the distances of color blocks can be determined directly based on the coordinates of the color blocks, and then the distances of the color blocks can be compared. The distance of the color blocks can also be the Euclidean distance determined based on the coordinates of the color blocks, which is the straight-line distance between the center points of the color blocks in the Euclidean space.

In step S13, all color blocks are clustered using the first color block and the second color block as cluster center points to obtain first category color blocks and second category color blocks;

The clustering process is to determine the color blocks that belong to the same category as the first color block, and to determine the color blocks that belong to the same category as the second color block, thereby obtaining the first category color blocks and the second category color blocks.

The clustering process can be specifically performed based on the positions of the color blocks. In a possible implementation, the first color block and the second color block are used as clustering centers, all the color blocks are clustered, and first category color blocks and second category color blocks are obtained, including: using the first color block and the second color block as clustering centers, based on the position of each color block, all the color blocks are clustered to obtain first category color blocks and second category color blocks.

In this implementation, based on the positions of the color blocks, the color blocks close to the first color block are clustered into the first category of color blocks, and the color blocks close to the second color block are clustered into the second category of color blocks. Since the distance between the first color block and the second color block is far, it is possible to quickly and accurately distinguish the color blocks in the two areas, thereby achieving accurate division of the areas to which the color blocks belong.

In a possible implementation, the method of clustering all color blocks with the first color block and the second color block as cluster center points respectively to obtain first category color blocks and second category color blocks includes: for all color blocks, respectively calculating the distance from each color block to the two cluster center points; classifying each color block into the class corresponding to the cluster center point with the smallest distance to obtain first category color blocks and second category color blocks; according to the positions of the first category color blocks and the second category color blocks, respectively determining the centroids of the first category color blocks and the second category color blocks as new cluster center points of the first category color blocks and the second category color blocks; iteratively executing the above process of calculating the distance to determine the new cluster center points until the iteration stop condition is met to obtain the reclassified first category color blocks and second category color blocks.

The iteration stop condition may be, for example, that the iteration reaches a preset number of times. In one example, since two cluster center points that meet the distance condition have been selected after step S12, the algorithm will converge quickly, and usually only three iterations are needed to accurately cluster the color blocks in the two color card areas into two categories. Therefore, the number of iterations may be preset to three times, and the iteration may be stopped after reaching three times, and the color blocks of the first category and the color blocks of the second category may be output. In addition, the iteration condition may also be other conditions, such as reaching a predetermined iteration time, etc.

In this implementation, the first category color block is the color block closest to the cluster center point of the first category, and the second category color block is the color block closest to the cluster center point of the second category. Since two cluster center points that meet the distance condition have been selected in step S12, the center points of two different color card areas can be quickly clustered.

In step S14, the first category color blocks and the second category color blocks are divided into two areas.

After obtaining the first category color block and the second category color block, the color blocks can be divided into two areas according to the coordinates of the two categories of color blocks. For example, for the color card image shown in FIG2 , the two categories of color blocks can be divided into upper and lower areas according to the y value of the color card.

In a possible implementation, when the distance condition is the two color blocks that are the farthest apart among all color blocks, then determining the first color block and the second color block among the color blocks according to the coordinates of the color blocks includes: determining the two color blocks that are the farthest apart among all color blocks as the first color block and the second color block according to the coordinates of the color blocks.

For example, the top row of color blocks and the bottom row of color blocks can be determined based on the y value of the color block, and then two pairs of color blocks with a diagonal relationship in the color card can be determined based on the x value of the color block. Among the two pairs of color blocks, the pair of color blocks with the largest difference in x value can be identified as the two color blocks with the farthest distance among all color blocks. In addition, the distance between the two coordinates can be directly calculated based on the coordinates of the center points of the two color blocks, thereby determining the two color blocks with the farthest distance among all color blocks.

Practice has shown that the two color blocks that are farthest apart in the color card must belong to different color card areas. In this implementation, the two color blocks that are farthest apart from all the color blocks are determined according to the coordinates of the color blocks as the first color block and the second color block, so that the center point of the cluster is the two color blocks that are farthest apart from all the color blocks. Therefore, the color blocks in the two areas can be accurately clustered to the cluster center point closest to themselves, so as to accurately distinguish the color blocks in different areas, thereby improving the accuracy of distinguishing the color card areas.

In a possible implementation, when the positional relationship between two color card areas is an upper and lower adjacent relationship, and when the distance condition is the longest longitudinal distance among all color blocks, then, determining the first color block and the second color block in the color blocks according to the coordinates of the color blocks includes: determining the color blocks with minimum and maximum longitudinal coordinates according to the longitudinal coordinates of the center points of the color blocks; determining the top row of color blocks and the bottom row of color blocks based on the minimum and maximum longitudinal coordinates; and selecting the color blocks in the top row of color blocks as the first color blocks, and selecting the color blocks in the bottom row of color blocks as the second color blocks based on the horizontal coordinates of the center points of the color blocks.

When the positional relationship between the two color card areas is an upper and lower adjacent relationship, and the cluster center points are located at the top row of color blocks and the bottom row of color blocks respectively, the efficiency of clustering based on position is faster, and the clustering result is more accurate. Therefore, the top row of color blocks and the bottom row of color blocks can be determined based on the maximum and minimum values of the longitudinal coordinates of the color block center points, and then the color blocks in the top row of color blocks can be selected as the first color blocks, and the color blocks in the bottom row of color blocks can be selected as the second color blocks. As a result, the longitudinal distance of the selected cluster center points is larger, so that the efficiency of clustering based on position is faster, and the clustering result is more accurate.

In one example, any color block in the top row of color blocks can be selected as the first color block, and any color block in the bottom row of color blocks can be selected as the second color block; in another example, the color block with the smallest horizontal coordinate in the top row of color blocks is selected as the first color block, and the color block with the largest horizontal coordinate in the bottom row of color blocks is selected as the first color block; or, the color block with the largest horizontal coordinate in the top row of color blocks is selected as the first color block, and the color block with the smallest horizontal coordinate in the bottom row of color blocks is selected as the first color block; or, based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block. Thus, a pair of color blocks located at the diagonal endpoints of the rectangular frame formed by the two color card areas can be selected as the cluster center points. Since the distance between the two cluster center points is not only large enough in the vertical direction, but also large enough in the horizontal direction, the efficiency of position-based clustering can be made faster, and the clustering result can be more accurate. Furthermore, the process is implemented based on comparing the horizontal and vertical coordinates of the center point of the color block, without using the coordinate values to calculate the distance of the color block, thereby improving the efficiency of determining the center point of the cluster.

In a possible implementation, the determining of the top row of color blocks and the bottom row of color blocks based on the minimum and maximum values of the ordinate includes: based on the minimum value of the ordinate, determining the color blocks whose ordinate values are within a first range as the top row of color blocks, the first range including: the minimum value of the ordinate minus half the color block size to the minimum value of the ordinate plus half the color block size; based on the maximum value of the ordinate, determining the color blocks whose ordinate values are within a second range as the bottom row of color blocks, the second range including: the maximum value of the ordinate minus half the color block size to the maximum value of the ordinate plus half the color block size.

Considering the influence of the shooting angle, the vertical coordinates of the color blocks in the top row are often not completely the same, and the vertical coordinates of the color blocks in the bottom row are often not completely the same. Therefore, when determining the color blocks in the top row, the color blocks with vertical coordinates within the first range can be determined based on the minimum vertical coordinate value as the color blocks in the top row. The endpoints of the first range here can be the minimum vertical coordinate value ±1/2 of the vertical size of the color block. The verification results show that when the color blocks in the top row are determined based on the first range, the color blocks in the top row can be accurately distinguished, and other color blocks will not be misjudged as the color blocks in the top row, with a high accuracy rate.

Similarly, when determining the bottom row of color blocks, the color blocks with ordinate values within the second range can be determined based on the minimum ordinate value as the bottom row of color blocks, where the endpoints of the second range can be the maximum ordinate value ±1/2 of the vertical size of the color block. Verification results show that when determining the bottom row of color blocks based on the second range, the bottom row of color blocks can be accurately distinguished, and other color blocks will not be misjudged as the bottom row of color blocks, with a high accuracy rate.

It should be noted that in the disclosed embodiment, the origin of the image coordinate system is located at the upper left corner of the image, the vertical direction is the Y axis, and the y value gradually increases from top to bottom; the horizontal direction is the X axis, and the x value gradually increases from left to right. Therefore, the maximum value of the vertical coordinate of the color block is used to determine the color block in the bottom row, and the minimum value of the vertical coordinate of the color block is used to determine the color block in the top row.

In the embodiment of the present disclosure, based on the minimum value of the ordinate, the color blocks with ordinate values within the first range are determined as the top row of color blocks; based on the maximum value of the ordinate, the color blocks with ordinate values within the second range are determined as the bottom row of color blocks. Thus, the top row of color blocks and the bottom row of color blocks can be accurately determined, reducing the possibility of missing color blocks, facilitating the subsequent clustering of color blocks based on the top row of color blocks and the bottom row of color blocks, improving the efficiency and accuracy of clustering, and improving the efficiency and accuracy of distinguishing color card areas.

In one possible implementation, the color card recognition method can be executed by electronic devices such as terminal devices and servers. The terminal device can be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. The method can be implemented by a processor calling a computer-readable instruction stored in a memory.

In addition, the present disclosure also provides a color card recognition device, an electronic device, a computer-readable storage medium, and a program, all of which can be used to implement any color card recognition method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to in the corresponding records of the method part and will not be repeated here.

FIG4 shows a block diagram of a color card recognition device according to an embodiment of the present disclosure. As shown in FIG4 , the device 40 includes:

A color block recognition module 41 is used to perform color block recognition on a color card image to obtain recognized color blocks, wherein the color card image includes two color card areas in the same color card tool;

A center point determination module 42, configured to determine a first color block and a second color block in the color blocks according to the coordinates of the color blocks, wherein the distance between the first color block and the second color block satisfies a distance condition;

A clustering module 43, configured to cluster all color blocks using the first color block and the second color block as cluster centers to obtain first category color blocks and second category color blocks;

The region division module 44 is used to divide the first category color blocks and the second category color blocks into two regions.

In a possible implementation, the center point determination module is used to:

According to the coordinates of the color block, two color blocks with the farthest distance from each other among all the color blocks are determined as the first color block and the second color block.

In a possible implementation, the center point determination module is used to:

According to the ordinate of the center point of the color block, the color blocks with the minimum and maximum ordinate values are determined respectively;

Based on the minimum and maximum values of the ordinate, determine the top row of color blocks and the bottom row of color blocks;

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, the center point determination module is used to:

Based on the minimum value of the ordinate, determine the color blocks whose ordinate values are within a first range as the color blocks in the top row, wherein the first range includes: the minimum value of the ordinate minus half the size of the color block to the minimum value of the ordinate plus half the size of the color block;

Based on the maximum ordinate value, determine the color blocks whose ordinate values are within a second range as the color blocks in the bottom row, where the second range includes: the maximum ordinate value minus half the color block size to the maximum ordinate value plus half the color block size.

In a possible implementation, the center point determination module is used to:

The color block with the smallest horizontal coordinate in the top row of color blocks is used as the first color block, and the color block with the largest horizontal coordinate in the bottom row of color blocks is used as the first color block; or,

The color block with the largest horizontal coordinate in the top row of color blocks is taken as the first color block, and the color block with the smallest horizontal coordinate in the bottom row of color blocks is taken as the first color block; or,

Based on the horizontal coordinate of the center point of the color block, the color block in the top row of color blocks is selected as the first color block, and the color block in the bottom row of color blocks is selected as the second color block.

In a possible implementation, the clustering module is used to:

The first color block and the second color block are used as cluster center points, and based on the position of each color block, all color blocks are clustered to obtain first category color blocks and second category color blocks.

In a possible implementation, the clustering module is used to:

For all color blocks, calculate the distance between each color block and the two cluster center points;

Classify each color block into the class corresponding to the cluster center point with the smallest distance, and obtain the first category color block and the second category color block;

According to the positions of the first category color blocks and the second category color blocks, respectively determine the centroids of the first category color blocks and the second category color blocks as new clustering center points of the first category color blocks and the second category color blocks;

The above process of calculating the distance to determine the new cluster center point is iteratively performed until the iteration stop condition is met, and the reclassified first category color blocks and second category color blocks are obtained.

In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

The embodiment of the present disclosure also provides a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the above method is implemented. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to call the instructions stored in the memory to execute the above method.

The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

The electronic device may be provided as a terminal, a server, or a device in other forms.

5 shows a block diagram of an electronic device 800 according to an embodiment of the present disclosure. For example, the electronic device 800 may be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or other terminal devices.

5 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input/output (I/O) interface 812 , a sensor component 814 , and a communication component 816 .

The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations on the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 800.

The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

I/O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open/closed state of the electronic device 800, the relative positioning of the components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration/deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a complementary metal oxide semiconductor (CMOS) or a charge coupled device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as a wireless network (Wi-Fi), a second generation mobile communication technology (2G), a third generation mobile communication technology (3G), a fourth generation mobile communication technology (4G), a long-term evolution (LTE) of a universal mobile communication technology, a fifth generation mobile communication technology (5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above method.

The present disclosure may be a system, a method and/or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can 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 thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing/processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and/or edge servers. The network adapter card or network interface in each computing/processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing/processing device.

The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

Various aspects of the present disclosure are described herein with reference to the flowcharts and/or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and/or block diagram and the combination of each box in the flowchart and/or block diagram can be implemented by computer-readable program instructions.

These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions/actions specified in one or more boxes in the flowchart and/or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and/or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions/actions specified in one or more boxes in the flowchart and/or block diagram.

Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions/actions specified in one or more boxes in the flowchart and/or block diagram.

The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and/or flow chart, and the combination of the square boxes in the block diagram and/or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) and the like.

The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

If the technical solution of this application involves personal information, the product using the technical solution of this application has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using the technical solution of this application has obtained the individual's separate consent before processing the sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, clear and prominent signs are set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that he or she agrees to the collection of his or her personal information; or on the device that processes personal information, the personal information processing rules are notified by obvious signs/information, and the individual's authorization is obtained through pop-up information or by asking the individual to upload his or her personal information; among them, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the type of personal information processed.

The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (10)

1. A color chart identification method, comprising:

Performing color lump recognition on the color lump image to obtain a recognized color lump, wherein the color lump image comprises two color lump areas in the same color lump tool;

determining a first color block and a second color block in the color blocks according to the coordinates of the color blocks, wherein the distance between the first color block and the second color block meets a distance condition;

clustering all color blocks by taking the first color block and the second color block as clustering center points respectively to obtain a first class color block and a second class color block;

dividing the first class color block and the second class color block into two areas;

and clustering all color blocks by taking the first color block and the second color block as clustering center points respectively to obtain a first class color block and a second class color block, wherein the method comprises the following steps:

based on the locations of the color patches, color patches that are closer to the first color patch are clustered into a first class of color patches, and color patches that are closer to the second color patch are clustered into a second class of color patches.

2. The method of claim 1, wherein determining a first color patch and a second color patch of the color patches based on coordinates of the color patches comprises:

And determining two color blocks with the farthest distance from all the color blocks according to the coordinates of the color blocks, and taking the two color blocks as a first color block and a second color block.

3. The method of claim 1, wherein determining a first color patch and a second color patch of the color patches based on coordinates of the color patches comprises:

Respectively determining color blocks with minimum and maximum values of the ordinate according to the ordinate of the center point of the color block;

determining an uppermost row of color blocks and a lowermost row of color blocks based on the ordinate minimum and maximum values;

Based on the abscissa of the center point of the color blocks, the color block in the uppermost row is selected as a first color block, and the color block in the lowermost row is selected as a second color block.

4. A method according to claim 3, wherein the values of the ordinate progressively increase from top to bottom and the values of the abscissa progressively increase from left to right, the determining the top and bottom rows of color blocks based on the ordinate minimum and maximum values comprising:

Determining, as the uppermost line of color patches, color patches having values of the ordinate within a first range based on the ordinate minimum, the first range including: decreasing the ordinate minimum by one half a color block size to the ordinate minimum plus one half a color block size;

Determining, based on the ordinate maximum, color patches having values of the ordinate within a second range, as a lowermost line of color patches, the second range comprising: the ordinate maximum decreases by one half the color tile size to the ordinate maximum plus one half the color tile size.

5. A method according to claim 3, wherein selecting the color block in the top row of color blocks as the first color block and the color block in the bottom row of color blocks as the second color block based on the abscissa of the center point of the color blocks comprises:

taking the color block with the smallest abscissa in the color block of the uppermost row as a first color block, and taking the color block with the largest abscissa in the color block of the lowermost row as a second color block; or alternatively, the first and second heat exchangers may be,

The color block with the largest abscissa in the color block of the uppermost row is taken as a first color block, and the color block with the smallest abscissa in the color block of the lowermost row is taken as a second color block.

6. The method according to claim 1, wherein clustering all color blocks with the first color block and the second color block as clustering center points to obtain a first class color block and a second class color block includes:

and clustering all color blocks based on the positions of the color blocks by taking the first color block and the second color block as clustering center points to obtain a first class color block and a second class color block.

7. The method according to claim 1, wherein clustering all color blocks with the first color block and the second color block as clustering center points to obtain a first class color block and a second class color block includes:

for all color blocks, respectively calculating the distances from each color block to two clustering center points;

classifying each color block into a class corresponding to a clustering center point with the smallest distance to obtain a first class color block and a second class color block;

according to the positions of the first-class color blocks and the second-class color blocks, the centroids of the first-class color blocks and the second-class color blocks are respectively determined and used as new clustering center points of the first-class color blocks and the second-class color blocks;

And iteratively executing the process of calculating the distance from each color block to the two clustering center points to serve as the new clustering center points of the first-class color block and the second-class color block until the iteration stop condition is met, and obtaining the reclassified first-class color block and second-class color block.

8. A color chart identification device, comprising:

the color lump identification module is used for carrying out color lump identification on the color lump image to obtain an identified color lump, and the color lump image comprises two color lump areas in the same color lump tool;

the center point determining module is used for determining a first color block and a second color block in the color blocks according to the coordinates of the color blocks, and the distance between the first color block and the second color block meets the distance condition;

the clustering module is used for clustering all color blocks by taking the first color block and the second color block as clustering center points respectively to obtain a first class color block and a second class color block;

the area dividing module is used for dividing the first class color block and the second class color block into two areas;

the clustering module is used for clustering color blocks close to the first color block into first class color blocks and clustering color blocks close to the second color block into second class color blocks based on the positions of the color blocks.

9. An electronic device, comprising:

A processor;

a memory for storing processor-executable instructions;

Wherein the processor is configured to invoke the instructions stored in the memory to implement the method of any of claims 1 to 7.

10. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 7.