System and method for determining dominant color in an image and non-transitory computer readable medium

Abstract

The present invention provides a system and method for determining a dominant color in an image and a non-transitory computer readable medium. The system includes a computing device configured to receive a digital image, divide the digital image into a plurality of pixel groups including at least a first pixel group and a second pixel group, analyze pixels in the first pixel group based on a first sampling rate, analyze pixels in the second pixel group based on a second sampling rate, and determine a dominant color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group. The pixels in the first pixel group are closer to a center of the image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate. The dominant color in an image determined according to the system and method of the present invention can mimic human perception of an image.

Description

[0001] This application is a divisional application of the invention patent filed on June 14, 2018, with application number "201810612826.1" and titled "System and method for determining the dominant color in an image and a non-transitory computer-readable medium".

[0002] Cross Reference to Related Applications

[0003] This application claims the rights of U.S. Provisional Application No. 62 / 519,615, filed June 14, 2017, and U.S. General Application No. 15 / 996,668, filed June 4, 2018.

[0004] The full disclosures of the aforementioned provisional application are incorporated herein by reference. Technical Field

[0005] The present invention relates to a system and method for determining the dominant color in a digital image, and more specifically, to a system and method for determining the dominant color in a digital image that can simulate human perception of an image. Background Technology

[0006] This section provides background information related to the present invention, which is not necessarily prior art.

[0007] When processing and analyzing digital images, it is useful to identify one or more dominant colors that appear in the image. For example, a digital image can be analyzed to determine a dominant color, which can then be matched with paint colors and used by consumers to purchase paint that matches the dominant color in the digital image.

[0008] Existing systems use mathematical algorithms to average the color values ​​of all pixels across an image. For example, hue, chroma, and lightness / darkness values ​​can be averaged to provide a representation of the colors across the entire image. However, this approach may produce colors with low chroma and / or emphasize background colors that differ from human perception of the image. Summary of the Invention

[0009] This section provides a general overview of the invention and is not a complete disclosure of its full scope or all its features.

[0010] The present invention provides a system including a computing device configured to: receive a digital image; divide the digital image into pixel groups including at least a first pixel group and a second pixel group; analyze pixels in the first pixel group based on a first sampling rate; analyze pixels in the second pixel group based on a second sampling rate; and determine the dominant color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group, wherein the pixels in the first pixel group are closer to the center of the image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

[0011] In some configurations, these groups also include a third pixel group, and the computing device is further configured to: analyze the pixels in the third pixel group based on a third sampling rate; and determine the dominant color of the digital image based on the analyzed pixels in the third pixel group, in addition to the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group, wherein the pixels in the third pixel group are farther from the center of the image than the pixels in the first pixel group and the pixels in the second pixel group, and wherein the third sampling rate is less than the second sampling rate.

[0012] In some configurations, the computing device is further configured to: generate a count of the color of each pixel in the first pixel group and the second pixel group; and determine the primary color of the digital image based on the pixel color with the largest corresponding count.

[0013] In some configurations, the computing device is further configured to: determine the chromaticity values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and exclude any pixel with a chromaticity value less than a predetermined chromaticity threshold from the analysis.

[0014] In some configurations, the computing device is further configured to: determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and exclude any pixel with a brightness value less than a predetermined brightness threshold from the analysis.

[0015] In some configurations, the computing device is further configured to: determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and exclude any pixel with a brightness value greater than a predetermined brightness threshold from the analysis.

[0016] In some configurations, the computing device is further configured to: determine the matching paint color that is closest to the primary color; and output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the primary color.

[0017] In another form, the invention provides a method comprising: receiving a digital image using a computing device. The method further comprises: dividing the digital image into a plurality of pixel groups, including at least a first pixel group and a second pixel group, using the computing device. The method further comprises: analyzing pixels in the first pixel group using the computing device based on a first sampling rate. The method further comprises: analyzing pixels in the second pixel group using the computing device based on a second sampling rate. The method further comprises: determining the dominant color of the digital image using the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group. The pixels in the first pixel group are closer to the center of the image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

[0018] In some configurations, the plurality of pixel groups further includes a third pixel group having pixels that are further away from the center of the image than those pixels in the first pixel group and those pixels in the second pixel group, and the method further includes: using a computing device to analyze the pixels in the third pixel group based on a third sampling rate, the third sampling rate being less than the second sampling rate; and using the computing device, in addition to the analyzed pixels in the first pixel group and the second pixel group, to determine the primary color of the digital image based on the analyzed pixels in the third pixel group.

[0019] In some configurations, the method includes: using the computing device to generate a count of the colors of each of the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group; and using the computing device to determine the dominant color of the digital image based on the pixel color having the largest corresponding count.

[0020] In some configurations, the method includes: using the computing device to determine the chromaticity values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and using the computing device to exclude any pixels with chromaticity values ​​less than a predetermined chromaticity threshold from the analysis.

[0021] In some configurations, the method includes: using a computing device to determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and using the computing device to exclude any pixels with brightness values ​​less than a predetermined brightness threshold from the analysis.

[0022] In some configurations, the method includes: using a computing device to determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and using the computing device to exclude any pixels with brightness values ​​greater than a predetermined brightness threshold from the analysis.

[0023] In some configurations, the method includes: using the computing device to determine the matching paint color that is closest to the primary color; and using the computing device to output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the primary color.

[0024] In another form, the invention provides a non-transitory computer-readable medium storing an application for a computing device. The application includes computer-executable instructions for configuring the computing device to perform the following operations: receiving a digital image; dividing the digital image into pixel groups comprising at least a first pixel group and a second pixel group; analyzing pixels in the first pixel group based on a first sampling rate; analyzing pixels in the second pixel group based on a second sampling rate; and determining the dominant color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group, wherein the pixels in the first pixel group are closer to the center of the image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

[0025] In some configurations, the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: generating a count of the colors of each of the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group; and determining the primary color of the digital image based on the pixel color having the largest corresponding count.

[0026] In some configurations, the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: determining the chromaticity values ​​of the pixels in the first pixel group and the pixels in the second pixel group, and excluding any pixels with chromaticity values ​​less than a predetermined chromaticity threshold from the analysis.

[0027] In some configurations, the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: determining the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group, and excluding any pixels with brightness values ​​less than a predetermined brightness threshold from the analysis.

[0028] In some configurations, the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: determining the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group, and excluding any pixels with brightness values ​​greater than a predetermined brightness threshold from the analysis.

[0029] In some configurations, the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: determining the matching paint color closest to the primary color; and outputting at least one of the paint color name and paint color identification code of the matching paint color closest to the primary color. Attached Figure Description

[0030] The accompanying drawings described herein are for illustrative purposes only, and not for all possible implementations, and are not intended to limit the scope of the invention.

[0031] Figure 1 This is a block diagram of the image analysis system according to the present invention.

[0032] Figure 2 This is a block diagram illustrating the analysis of pixels in an image by an image analysis system according to the present invention.

[0033] Figure 3 This is a flowchart of an image analysis method according to the present invention.

[0034] Throughout the several views in the accompanying drawings, corresponding reference numerals indicate the respective parts. Detailed Implementation

[0035] Exemplary embodiments will now be described more fully with reference to the accompanying drawings.

[0036] This invention provides a system and method for determining the dominant color in an image. (Reference) Figure 1 The diagram illustrates a system 10 for determining the dominant color in an image. System 10 may include a computing device 1302. This computing device may be a personal computer, laptop computer, mobile device, desktop computer, or other suitable computing device having a processor and memory for performing the functions described herein. The computing device includes an image analysis module 14. The image analysis module 14 may, for example, be implemented as part of a mobile application on mobile device 14, as part of a web application running in a browser on computing device 12, or as part of a standalone application running on computing device 12.

[0037] Image analysis module 14 receives digital image 16 as input. Image analysis module 14 analyzes the received image and generates output 18 indicating one or more primary colors from image 16.

[0038] Specifically, the image analysis module 14 analyzes each pixel within the image file, starting from the center of the image and working outwards in a spiral manner. As the image analysis module 14 moves further away from the center of the image, the sampling rate decreases, causing pixels towards the image center to be sampled at a higher rate than pixels towards the image edges. In this way, pixels near the center are weighted more heavily than pixels far from the center and towards the image edges. Furthermore, low-level chromaticity colors (i.e., very dark or soft) such as those with colors below a predetermined chromaticity value threshold are excluded. Additionally, low-brightness colors (i.e., very dark) such as those with brightness levels below a brightness threshold are also excluded. Furthermore, high-brightness colors (i.e., very bright) such as those with brightness levels above a brightness threshold are also excluded. All remaining sampled colors are counted, with similar colors grouped together. The image analysis module 14 then determines the color or group of similar colors with the highest count and returns the representation of this color or group of similar colors as the dominant color of the image.

[0039] refer to Figure 2 Example image 20 is shown, broken down into individual pixel squares labeled by columns and rows, in the following format: row, column. For example, the top-left pixel is labeled as row, column: 1, 1. The top-right pixel is labeled as row, column: 1, 5. The bottom-left pixel is labeled as row, column: 7, 1. The bottom-right pixel is labeled as row, column: 7, 5. Although an image with seven rows and five columns is used as an example here, in reality, digital images can have a much larger number of pixels.

[0040] In this example, the order of analysis is indicated by arrows and begins at pixel 4,3 in the center of the image. Pixels included in the image analysis are shown as white squares. Pixels skipped or excluded from the analysis are shown in gray.

[0041] Starting from the center of image 20, image analysis module 14 includes the first four pixels in the analysis (i.e., 4, 3; 4, 4; 5, 4; and 5, 3). Then, starting from pixel 5, 2, image analysis module 1304 begins analyzing every other pixel. In other words, after pixel 5, 3, the next four pixels analyzed are: 4, 2; 3, 3; 3, 5; and 5, 5. Then, starting from pixel 6, 5, image analysis module 14 begins skipping two pixels for each pixel included in the analysis. For example, after pixel 5, 5, the next five pixels analyzed are: 6, 3; 5, 1; 2, 1; 2, 4; and 7, 4. Then, starting from pixel 7, 4, image analysis module 14 begins skipping three pixels for each pixel being analyzed. Similarly, after 7, 4, the next three pixels analyzed are: 1, 1 and 1, 5.

[0042] In this way, the image analysis module 14 reduces the pixel sampling rate by skipping more and more pixels as it moves away from the center of the image. For the remaining unskipped pixels, the image analysis module 14 applies the aforementioned filters for low chroma values, low brightness values, and high brightness values. The remaining pixels are then analyzed, where similar pixel colors are grouped together. Based on the number of color or similar pixel color groups, the image analysis module then determines one or more dominant colors of the image 20.

[0043] refer to Figure 3 A method 30 for analyzing an image according to the present invention is shown. Method 30 can be executed by an image analysis module 14 of a computing device 12 and begins at point 32. At point 34, the image analysis module 14 receives an image 16. At point 36, the image analysis module 14 divides the pixels of the image into subgroups, each of which is analyzed using a different sampling rate. Figure 2 The example image will have the following subgroups: First subgroup: 4, 3; 4, 4; 5, 4; and 5, 3. Second subgroup: 5, 2; 4, 2; 3, 2; 3, 3; 3, 4; 3, 5; 4, 5; and 5, 5. Third subgroup: 6, 5; 6, 4; 6, 3; 6, 2; 6, 1; 5, 1; 4, 1; 3, 1; 2, 1; 2, 2; 2, 3; 2, 4; 2, 5; 7, 5 and 7, 4. Fourth subgroup: 7, 3; 7, 2; 7, 1; 1, 1; 1, 2; 1, 3; 1, 4; and 1, 5.

[0044] At position 38, the image analysis module 14 uses different sampling rates to analyze different subgroups. For example, it analyzes every pixel in the first subgroup; every other pixel in the second subgroup; every third pixel in the third subgroup; and every fourth pixel in the fourth subgroup. (Although reference...) Figure 2 and Figure 3 Four different sampling rates are described for four different subgroups, but any number of subgroups with any number of pixels and any number of sampling rates can be used. Furthermore, the image analysis module 14 can use different processing threads to perform analysis on various subgroups simultaneously.

[0045] Also at point 38, each pixel is analyzed based on the exclusion rules discussed above. For example, any pixel with a chromaticity value below the chromaticity threshold and that is too dark or soft is excluded. Any pixel with a luminance value below the luminance threshold and that is too dark is excluded. Any pixel with a luminance value above the luminance threshold and that is too bright is excluded. Furthermore, similar colors (i.e., colors with hue, chromaticity, and luminance / darkness values ​​within predetermined thresholds for each other) are grouped together. For each subgroup, the total number of different colors or similar color groups is counted by the image analysis module 14.

[0046] At 40 locations, the total number from each subgroup is combined to make groups of the same or similar colors added together.

[0047] At position 42, the image analysis module 14 then determines one or more primary colors based on the total number. In other words, the color or color group with the highest total number is considered the primary color of the image.

[0048] In some embodiments, computing device 12 may then determine the closest matching paint color to the determined primary color. For example, computing device 12 may access a paint color database and search the database to find the closest matching paint color to the determined primary color by comparing the color value of the determined primary color (e.g., RBG (red, green, blue) color value, CMYK (cyan, magenta, yellow, and positional chroma / black) color value, and / or CIE XYZ color value) with the color values ​​of various paint colors in the paint color database. For example, a system and method for determining the closest matching paint color to a particular color are described in commonly assigned U.S. Patent No. 9,928,543, entitled "Data-Driven Color Coordinator," published March 27, 2018, which is incorporated herein by reference in its entirety.

[0049] The method ends at point 44.

[0050] The foregoing description of specific embodiments has been provided for purposes of illustration and description. This description is not intended to be exhaustive or limiting of the invention. Individual elements or features of a particular embodiment are generally not limited to that particular embodiment, but are interchangeable and can be used in selected embodiments where applicable, even if not specifically shown or described. The same elements or features may also be varied in many ways. Such variations are not considered to depart from the invention, and all such variations are intended to be included within the scope of the invention.

[0051] The terms computing devices and modules may refer to or be part of or include application-specific integrated circuits (ASICs); digital, analog, or mixed-signal analog / digital discrete circuits; digital, analog, or mixed-signal analog / digital integrated circuits; combinational logic circuits; field-programmable gate arrays (FPGAs); (shared, dedicated, or group) processors that execute code; (shared, dedicated, or group) memory that stores code executed by the processor; other suitable hardware components that provide the described functionality; or combinations of some or all of the above, such as on a system-on-a-chip.

[0052] As used above, the term "code" can include software, firmware, and / or microcode, and can refer to programs, routines, functions, classes, and / or objects. The term "shared processor" covers a single processor that executes some or all of the code from multiple modules. The term "group processor" covers a processor, in combination with additional processors, that executes some or all of the code from one or more modules. The term "shared memory" covers a single memory that stores some or all of the code from multiple modules. The term "group memory" covers a memory, in combination with additional memory, that stores some or all of the code from one or more modules. The term "memory" can be a subset of the term "computer-readable medium." The term "computer-readable medium" does not cover transient electronic and electromagnetic signals propagating through a medium and can therefore be considered tangible and non-transient. Non-limiting examples of non-transient tangible computer-readable media include non-volatile memory, volatile memory, magnetic storage devices, and optical storage devices.

[0053] The services, user equipment, apparatus, and methods described in this invention can be implemented, in part or in whole, using or by one or more computer programs executed by one or more processors. The computer program includes processor-executable instructions stored on at least one non-transitory tangible computer-readable medium. The computer program may also include and / or depend on stored data.

[0054] The provision of exemplary embodiments makes the invention thorough and will fully convey its scope to those skilled in the art. Numerous specific details (such as examples of specific components, devices, and methods) are set forth to provide a thorough understanding of embodiments of the invention. It will be apparent to those skilled in the art that the specific details are not necessary, that the exemplary embodiments may be implemented in many different forms, and that neither should be construed as limiting the scope of the invention. In some exemplary embodiments, well-known processes, well-known device structures, and well-known techniques have not been described in detail.

[0055] The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” may be intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms “comprises,” “comprising,” “including,” and “having” are inclusive and therefore specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. The method steps, processes, and operations described herein should not be construed as requiring them to be performed in the particular order discussed or shown, unless specifically identified as such. It should also be understood that additional or alternative steps may be employed.

[0056] Spatial terms such as “inner,” “outer,” “below,” “below,” “above,” and “upper” may be used herein to simplify descriptions of the relationship between an element or feature and other elements(s) or features(s), as illustrated in the accompanying drawings. Spatial terms may be intended to cover different orientations of the device in use or operation, other than those depicted in the drawings. For example, if the device in the drawings is flipped, an element described as “below” or “below” other elements or features will be oriented “above” those other elements or features. Thus, the example term “below” can encompass both above and below orientations. The device may be oriented in other ways (rotated 90 degrees or in other orientations), and the spatially related descriptive terms used herein should be interpreted accordingly.

Claims

1. A method for determining the dominant color in an image, comprising: Using a computing device to analyze pixels in a first pixel group of a digital image based on a first sampling rate; The computing device is used to analyze pixels in a second pixel group of the digital image based on a second sampling rate; as well as The computing device is used to determine the primary color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group; In this configuration, the pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

2. The method of claim 1, further comprising: The digital image is received using the computing device; as well as The computing device is used to divide the digital image into multiple pixel groups, including at least the first pixel group and the second pixel group.

3. The method of claim 1, further comprising: The computing device is used to analyze pixels in a third pixel group of the digital image based on a third sampling rate, which is less than the second sampling rate; as well as In addition to the pixels analyzed in the first pixel group and the pixels analyzed in the second pixel group, the computing device also determines the primary color of the digital image based on the pixels analyzed in the third pixel group; The pixels in the third pixel group are farther from the center of the digital image than the pixels in the first pixel group and the pixels in the second pixel group.

4. The method of claim 1, further comprising: The computing device is used to generate a count of the color of each pixel in the first pixel group and the second pixel group. as well as The computing device is used to determine the primary color of the digital image based on the pixel color with the largest corresponding count.

5. The method of claim 1, further comprising: The computing device is used to determine the chromaticity values ​​of the pixels in the first pixel group and the pixels in the second pixel group; as well as The computing device is used to exclude any pixel with a chromaticity value less than a predetermined chromaticity threshold from the analysis.

6. The method of claim 1, further comprising: The computing device is used to determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; as well as The computing device is used to exclude any pixel with a brightness value less than a predetermined brightness threshold from the analysis.

7. The method of claim 1, further comprising: The computing device is used to determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; as well as The computing device is used to exclude any pixel with a brightness value greater than a predetermined brightness threshold from the analysis.

8. The method of claim 1, further comprising: The computing device is used to determine the matching paint color that is closest to the primary color; as well as The computing device is used to output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the main color.

9. The method of claim 1, wherein, The computing device is a mobile device with a mobile application that configures the computing device to perform analysis of pixels in the first pixel group, analysis of pixels in the second pixel group, and determination of the primary color.

10. A non-transitory computer-readable medium storing an application for a computing device, the application including computer-executable instructions for configuring the computing device to perform the following operations: Analyze the pixels in the first pixel group of the digital image based on the first sampling rate; Analyze the pixels in the second pixel group of the digital image based on the second sampling rate; and The primary color of the digital image is determined based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group; in, The pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

11. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Receive the digital image; and The digital image is divided into multiple pixel groups, including at least the first pixel group and the second pixel group.

12. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Analyze pixels in a third pixel group of the digital image based on a third sampling rate, wherein the third sampling rate is less than the second sampling rate; and In addition to the pixels analyzed in the first pixel group and the pixels analyzed in the second pixel group, the primary color of the digital image is also determined based on the pixels analyzed in the third pixel group; in, The pixels in the third pixel group are farther from the center of the digital image than the pixels in the first pixel group and the pixels in the second pixel group.

13. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Generate a count of the color of each pixel in the first pixel group and the second pixel group; and The primary color of the digital image is determined based on the pixel color that has the largest corresponding count.

14. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Determine the chromaticity values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and Any pixel with a chromaticity value less than a predetermined chromaticity threshold is excluded from the analysis.

15. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: The computing device is used to determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and The computing device is used to exclude any pixel with a brightness value less than a predetermined brightness threshold from the analysis.

16. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Determine the brightness values ​​of the pixels in the first pixel group and the pixels in the second pixel group; and Any pixel with a brightness value greater than a predetermined brightness threshold is excluded from the analysis.

17. The non-transitory computer-readable medium of claim 10, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Determine the matching paint color that is closest to the primary color; and Output at least one of the paint color name and paint color identification code of the paint color that is closest to the main color.

18. A system for determining the dominant color in an image, comprising: A computing device is configured to analyze pixels in a first pixel group of a digital image based on a first sampling rate; The pixels in the second pixel group of the digital image are analyzed based on the second sampling rate; And determine the primary color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group; In this configuration, the pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group, and the first sampling rate is greater than the second sampling rate.

19. The system of claim 18, wherein, The computing device is further configured to receive the digital image and divide the digital image into a plurality of pixel groups, including at least the first pixel group and the second pixel group.

20. The system of claim 18, wherein, The computing device is further configured to: analyze pixels in a third pixel group of the digital image based on a third sampling rate, the third sampling rate being less than the second sampling rate; and determine the primary color of the digital image based on the analyzed pixels in the third pixel group, in addition to the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group. The pixels in the third pixel group are farther from the center of the digital image than the pixels in the first pixel group and the pixels in the second pixel group.

21. A method for determining the dominant color in an image, comprising: Using a computing device, the pixels of a digital image are divided into multiple pixel groups, including a first pixel group and a second pixel group, wherein the pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group; The computing device is used to compare the chromaticity values ​​of the pixels in the first pixel group and the second pixel group with a predetermined chromaticity value threshold. The computing device is used to compare the brightness values ​​of the pixels in the first pixel group and the second pixel group with a low brightness threshold and a high brightness threshold; The computing device is used and a first sampling rate is used to analyze pixels in the first pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; Using the computing device and a second sampling rate, analyze pixels in the second pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold, wherein the first sampling rate is greater than the second sampling rate; and The computing device is used to determine the primary color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group.

22. The method of claim 21, wherein, The plurality of pixel groups further includes a third pixel group, the third pixel group having pixels that are further away from the center of the digital image compared to the pixels in the first pixel group and the second pixel group, and the method further includes: The computing device is used to compare the chromaticity values ​​of the pixels in the third pixel group with the predetermined chromaticity value threshold. The computing device is used to compare the brightness values ​​of the pixels in the third pixel group with a low brightness threshold and a high brightness threshold; Using the computing device and a third sampling rate, analyze pixels in the third pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; and In addition to the pixels analyzed in the first and second pixel groups, the computing device also determines the primary color of the digital image based on the pixels analyzed in the third pixel group.

23. The method of claim 21, further comprising: The computing device is used to generate a count of the color of each pixel in the first pixel group and the second pixel group. as well as The computing device is used to determine the primary color of the digital image based on the pixel color with the largest corresponding count.

24. The method of claim 21, further comprising: The computing device is used to determine the matching paint color that is closest to the primary color; as well as The computing device is used to output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the main color.

25. The method of claim 21, wherein, The computing device is a mobile device with a mobile application that configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

26. The method of claim 21, wherein, The computing device has a web application that runs in the browser of the computing device and configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

27. The method of claim 21, wherein, The computing device has an application that, when executed, configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group, as well as to determine the primary color.

28. A non-transitory computer-readable medium storing an application for a computing device, the application including computer-executable instructions for configuring the computing device to perform the following operations: The pixels of a digital image are divided into multiple pixel groups, including a first pixel group and a second pixel group, where... The pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group; The chromaticity values ​​of the pixels in the first pixel group and the second pixel group are compared with a predetermined chromaticity value threshold. The brightness values ​​of the pixels in the first pixel group and the second pixel group are compared with the low brightness threshold and the high brightness threshold. The first sampling rate is used to analyze pixels in the first pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; The second sampling rate is used to analyze pixels in the second pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold, wherein the first sampling rate is greater than the second sampling rate. as well as The primary color of the digital image is determined based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group.

29. The non-transitory computer-readable medium of claim 28, wherein, The plurality of pixel groups further includes a third pixel group having pixels that are further away from the center of the digital image compared to the pixels in the first pixel group and the second pixel group, and the application further includes computer-executable instructions for configuring the computing device to perform the following operations: The chromaticity values ​​of the pixels in the third pixel group are compared with the predetermined chromaticity value threshold. The brightness values ​​of the pixels in the third pixel group are compared with the low brightness threshold and the high brightness threshold; A third sampling rate is used to analyze pixels in the third pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; as well as In addition to the pixels analyzed in the first and second pixel groups, the primary color of the digital image is also determined based on the pixels analyzed in the third pixel group.

30. The non-transitory computer-readable medium of claim 28, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Generate a count of the color of each pixel in the first pixel group and the second pixel group; and The primary color of the digital image is determined based on the pixel color that has the largest corresponding count.

31. The non-transitory computer-readable medium of claim 28, wherein the application further includes computer-executable instructions for further configuring the computing device to perform the following operations: Determine the matching paint color that is closest to the primary color; and Output at least one of the paint color name and paint color identification code of the paint color that is closest to the main color.

32. The non-transitory computer-readable medium of claim 28, wherein, The computing device is a mobile device and the application is a mobile application that configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

33. The non-transitory computer-readable medium of claim 28, wherein, The application is a web application that runs in the browser of the computing device and configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

34. A computing device configured to: The pixels of a digital image are divided into multiple pixel groups, including a first pixel group and a second pixel group, where... The pixels in the first pixel group are closer to the center of the digital image than the pixels in the second pixel group; The chromaticity values ​​of the pixels in the first pixel group and the second pixel group are compared with a predetermined chromaticity value threshold. The brightness values ​​of the pixels in the first pixel group and the second pixel group are compared with the low brightness threshold and the high brightness threshold. The first sampling rate is used to analyze pixels in the first pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; The second sampling rate is used to analyze pixels in the second pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold, wherein the first sampling rate is greater than the second sampling rate. as well as The computing device is used to determine the primary color of the digital image based on the analyzed pixels in the first pixel group and the analyzed pixels in the second pixel group.

35. The computing device of claim 34, wherein, The plurality of pixel groups further includes a third pixel group having pixels that are further away from the center of the digital image compared to the pixels in the first pixel group and the second pixel group, and the computing device is further configured to: The chromaticity values ​​of the pixels in the third pixel group are compared with the predetermined chromaticity value threshold. The brightness values ​​of the pixels in the third pixel group are compared with the low brightness threshold and the high brightness threshold; A third sampling rate is used to analyze pixels in the third pixel group that have a chromaticity value greater than the predetermined chromaticity value threshold and a brightness greater than the low brightness threshold and less than the high brightness threshold; as well as In addition to the pixels analyzed in the first and second pixel groups, the primary color of the digital image is also determined based on the pixels analyzed in the third pixel group.

36. The computing device of claim 34, wherein, The computing device is further configured to: Generate a count of the color of each pixel in the first pixel group and the second pixel group; and The primary color of the digital image is determined based on the pixel color that has the largest corresponding count.

37. The computing device of claim 34, wherein, The computing device is further configured to: Determine the matching paint color that is closest to the primary color; and Output at least one of the paint color name and paint color identification code of the paint color that is closest to the main color.

38. The computing device of claim 34, wherein, The computing device is a mobile device with a mobile application that configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

39. The computing device of claim 34, wherein, The computing device has a web application that runs in the browser of the computing device and configures the computing device to perform analysis of pixels in the first pixel group and the second pixel group and to determine the primary color.

40. The computing device of claim 34, wherein, The computing device is further configured to perform analysis of pixels in the first pixel group and the second pixel group, and to determine the primary color.

41. A computing device configured to: Divide the digital image into multiple pixel groups, including at least a first group of pixels and a second group of pixels; Pixels in the first group of pixels are selected based on the first sampling rate; The pixels in the second group of pixels are selected based on a second sampling rate, wherein the pixels in the first group of pixels are closer to the center of the image than the pixels in the second group of pixels, and the first sampling rate is greater than the second sampling rate; At least one filter is applied to selected pixels in the first group of pixels and the second group of pixels. The at least one filter includes at least one of the following: a chroma filter that removes pixels with chroma values ​​below a chroma threshold, a low brightness filter that removes pixels with brightness values ​​below a low brightness threshold, and a high brightness filter that removes pixels with brightness values ​​above a high brightness threshold. After applying the at least one filter, the remaining pixels selected from the first group of pixels and the second group of pixels are grouped into multiple groups, such that pixels having hue, chroma, and luminance values ​​within predetermined thresholds of each other are grouped together; as well as The primary color of the digital image is determined based on the color associated with the group that has the largest number of pixels among the plurality of groups.

42. The computing device of claim 41, wherein, The computing device is further configured to: determine the matching paint color that is closest to the primary color; and output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the primary color.

43. The computing device of claim 41, wherein, The computing device is configured to use different processing threads to select pixels from the first group of pixels based on the first sampling rate and to select pixels from the second group of pixels based on the second sampling rate.

44. The computing device of claim 41, wherein, The computing device is a mobile device with a mobile application that configures the computing device to divide the digital image into multiple pixel groups, select pixels in the first group of pixels, select pixels in the second group of pixels, apply the at least one filter, group the pixels in the remaining pixels, and determine the primary color of the digital image.

45. The computing device of claim 41, wherein, The computing device has a web application that runs in the browser of the computing device and configures the computing device to divide the digital image into multiple pixel groups, select pixels in the first group of pixels, select pixels in the second group of pixels, apply the at least one filter, group the pixels in the remaining pixels, and determine the primary color of the digital image.

46. ​​The computing device of claim 41, wherein, The computing device has an application that, when executed, configures the computing device to divide the digital image into multiple pixel groups, select pixels in the first group of pixels, select pixels in the second group of pixels, apply the at least one filter, group the pixels in the remaining pixels, and determine the primary color of the digital image.

47. A method for determining the dominant color in an image, comprising: Using a computing device, a digital image is divided into multiple pixel groups, including at least a first group of pixels and a second group of pixels; The computing device is used to select pixels from the first group of pixels based on a first sampling rate; The computing device is used to select pixels in the second group of pixels based on a second sampling rate, wherein pixels in the first group of pixels are closer to the center of the image than pixels in the second group of pixels, and the first sampling rate is greater than the second sampling rate; The computing device is used to apply at least one filter to selected pixels of the first group of pixels and the second group of pixels. The at least one filter includes at least one of the following: a chroma filter that removes pixels with chroma values ​​below a chroma threshold, a low brightness filter that removes pixels with brightness values ​​below a low brightness threshold, and a high brightness filter that removes pixels with brightness values ​​above a high brightness threshold. Using the computing device, pixels from the remaining pixels selected from the first group of pixels and the second group of pixels after applying the at least one filter are grouped into multiple groups, such that pixels having hue, chroma, and luminance values ​​within predetermined thresholds of each other are grouped together; as well as The computing device is used to determine the primary color of the digital image based on the color associated with the group that has the largest number of pixels among the plurality of groups.

48. The method of claim 47, further comprising: The computing device is used to determine the matching paint color that is closest to the primary color; as well as The computing device is used to output at least one of the paint color name and paint color identification code of the matching paint color that is closest to the main color.

49. The method of claim 47, wherein, Selecting pixels from the first group of pixels based on the first sampling rate and selecting pixels from the second group of pixels based on the second sampling rate are performed using different processing threads of the computing device.

50. The method of claim 47, wherein, The computing device is a mobile device with a mobile application, which performs the following operations: dividing the digital image into multiple pixel groups, selecting pixels from the first group of pixels, selecting pixels from the second group of pixels, applying the at least one filter, grouping the pixels in the remaining pixels, and determining the primary color of the digital image.

51. The method of claim 47, wherein, The computing device has a web application that runs in the browser of the computing device and performs the following operations: dividing the digital image into multiple pixel groups, selecting pixels in the first group of pixels, selecting pixels in the second group of pixels, applying the at least one filter, grouping the pixels in the remaining pixels, and determining the primary color of the digital image.

52. The method of claim 47, wherein, The computing device has an application that, when executed, configures the computing device to perform the following operations: dividing the digital image into multiple pixel groups, selecting pixels from the first group of pixels, selecting pixels from the second group of pixels, applying the at least one filter, grouping the pixels in the remaining pixels, and determining the primary color of the digital image.

53. A non-transitory computer-readable medium storing an application for a computing device, the application including computer-executable instructions for configuring the computing device to perform the following operations: Divide the digital image into multiple pixel groups, including at least a first group of pixels and a second group of pixels; Pixels in the first group of pixels are selected based on the first sampling rate; The pixels in the second group of pixels are selected based on a second sampling rate, wherein the pixels in the first group of pixels are closer to the center of the image than the pixels in the second group of pixels, and the first sampling rate is greater than the second sampling rate; At least one filter is applied to selected pixels in the first group of pixels and the second group of pixels. The at least one filter includes at least one of the following: a chroma filter that removes pixels with chroma values ​​below a chroma threshold, a low brightness filter that removes pixels with brightness values ​​below a low brightness threshold, and a high brightness filter that removes pixels with brightness values ​​above a high brightness threshold. After applying the at least one filter, the remaining pixels selected from the first group of pixels and the second group of pixels are grouped into multiple groups, such that pixels having hue, chroma, and luminance values ​​within predetermined thresholds of each other are grouped together; as well as The primary color of the digital image is determined based on the color associated with the group that has the largest number of pixels among the plurality of groups.

54. The non-transitory computer-readable medium of claim 53, wherein, The computer-executable instructions further configure the computing device to determine the matching paint color closest to the primary color, and output at least one of the paint color name and paint color identification code of the matching paint color closest to the primary color.

55. The non-transitory computer-readable medium of claim 53, wherein, The computer-executable instructions further configure the computing device to use different processing threads to select pixels in the first group of pixels based on the first sampling rate and to select pixels in the second group of pixels based on the second sampling rate.

56. The non-transitory computer-readable medium of claim 53, wherein, The computing device is a mobile device and the computer-executable instructions are contained in the mobile application.

57. The non-transitory computer-readable medium of claim 53, wherein, The computing device and the computer-executable instructions are contained in a web application that runs in a browser on the computing device.

58. The non-transitory computer-readable medium of claim 53, wherein, The computing device and the computer-executable instructions are included in an application that, when executed, configures the computing device to divide the digital image into multiple pixel groups, select pixels in the first group of pixels, select pixels in the second group of pixels, apply the at least one filter, group the pixels in the remaining pixels, and determine the primary color of the digital image.

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