Image information retrieval method and system based on local matching

Abstract

The invention is suitable for the technical field of image retrieval, and provides an image information retrieval method and system based on local matching, and the method comprises the following steps: receiving target images, carrying out the feature recognition of each target image, obtaining the feature information, carrying out the intersection processing of the color sets of all target images, obtaining the intersection color features, and carrying out the image retrieval. Determining an extra color set corresponding to each piece of feature information; preliminarily screening the images in the image library based on the intersection color features to obtain a preliminary retrieval image; performing secondary screening on the preliminary retrieval image based on the extra color set to obtain a secondary retrieval image; stroking the intersection color features in the secondary retrieval image and the colors in the additional color set to obtain a retrieval contour of each color; and performing similarity calculation on the secondary retrieval image based on the contour features. Therefore, similarity calculation is carried out only based on the contour of the effective color, the calculation amount is reduced, interference of other colors is eliminated, and the retrieval result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of image retrieval, and in particular to an image information retrieval method and system based on local matching. Background Art

[0002] When users use image retrieval, they have the following requirements: given a target image, retrieve a picture containing the target image, and the part of the picture that matches the target image. Most existing image retrieval technologies extract global features based on the entire image, obtain feature vectors that can represent image information, and then perform similarity retrieval. This global retrieval easily leads to low similarity between the picture containing the target image and the target image itself, especially when the picture itself is complex and the target image accounts for a small proportion, the retrieval accuracy is not high enough; and the image detection method based on global features for similarity matching requires a large amount of calculation, and the retrieval is not efficient enough. Therefore, it is necessary to provide an image information retrieval method and system based on local matching to solve or alleviate the above problems. Summary of the invention

[0003] In view of the deficiencies in the prior art, the object of the present invention is to provide an image information retrieval method and system based on local matching to solve or alleviate the problems existing in the above-mentioned background technology.

[0004] The present invention is implemented as follows: a method for image information retrieval based on local matching, the method comprising the following steps:

[0005] Receive a number of target images at different angles, perform feature recognition on each target image, and obtain feature information, wherein the feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to the number of color blocks;

[0006] Perform intersection processing on the color sets of all target images to obtain intersection color features, and determine the additional color set corresponding to each feature information based on the intersection color features;

[0007] Preliminarily screening the images in the image library based on the intersection color feature to obtain a preliminary retrieval image;

[0008] Perform secondary screening on the preliminary retrieval image based on the additional color set to obtain a secondary retrieval image, and classify the secondary retrieval image according to the additional color set, and each category corresponds to feature information;

[0009] The intersection color features in the secondary retrieval image and the colors in the additional color set are traced to obtain the retrieval outline of each color, and the number of color blocks corresponding to each color is determined;

[0010] The similarity of the secondary retrieval image is calculated based on the number of color blocks and contour features, and the final retrieval image is output according to the calculation results.

[0011] As a further solution of the present invention: the step of performing feature recognition on each target image to obtain feature information specifically includes:

[0012] Identify the colors contained in the target image and obtain a color set;

[0013] Stroke the edge of each color to obtain the contour features of each color;

[0014] The number of color blocks is determined according to the number of contours in the contour feature of each color, and the feature information is obtained according to the color set, the contour feature and the number of color blocks.

[0015] As a further solution of the present invention: the step of performing secondary screening on the primary search image based on the additional color set to obtain the secondary search image, and classifying the secondary search image according to the additional color set specifically includes:

[0016] Retrieve an additional color set corresponding to each feature information, wherein the additional color set includes zero, one, or multiple additional colors;

[0017] Arrange the extra color set in descending order according to the number of extra color types;

[0018] Perform secondary screening on the preliminary retrieval images according to the descending order to obtain secondary retrieval images, each of which corresponds to an additional color set;

[0019] The secondary retrieval images are classified according to the additional color sets, one for each category.

[0020] As a further solution of the present invention: the step of performing secondary screening on the preliminary search images according to the descending order to obtain the secondary search images specifically includes:

[0021] Determine the additional set of colors that are ranked first according to the descending order;

[0022] Performing a secondary screening on the preliminary search image according to the additional colors in the additional color set to obtain a secondary search image corresponding to the additional color set;

[0023] Eliminating the obtained secondary retrieval image from the preliminary retrieval image, and excluding the additional color set from the descending order;

[0024] Repeat the above three steps until the secondary retrieval image is empty or the additional color set in descending order is empty.

[0025] As a further solution of the present invention: the step of calculating the similarity of the secondary retrieval image based on the number of color blocks and the contour features specifically includes:

[0026] Determining feature information corresponding to the secondary search image, and screening the secondary search image based on the number of color blocks of the feature information;

[0027] Calculating the contour similarity between the retrieval contour of each color in the screened secondary retrieval image and the contour feature of each color in the feature information;

[0028] The average value of the contour similarities of all colors is calculated to obtain the calculation result.

[0029] As a further solution of the present invention: the step of screening the secondary search image based on the number of color blocks of the feature information specifically includes:

[0030] Comparing the number of color blocks of each color in the feature information with the number of color blocks of the corresponding color in the secondary retrieval image;

[0031] When the number of color blocks of any color in the feature information is greater than K×the number of color blocks of the corresponding color in the secondary retrieval image, where K is a constant value greater than 1, the corresponding secondary retrieval image is deleted.

[0032] Another object of the present invention is to provide an image information retrieval system based on local matching, the system comprising:

[0033] The target image uploading module is used to receive a number of target images at different angles, perform feature recognition on each target image, and obtain feature information, wherein the feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to the number of color blocks;

[0034] An intersection color feature module is used to perform intersection processing on the color sets of all target images to obtain intersection color features, and determine the additional color set corresponding to each feature information based on the intersection color features;

[0035] An image preliminary retrieval module, used for performing preliminary screening of images in an image library based on the intersection color feature to obtain a preliminary retrieval image;

[0036] The image secondary retrieval module is used to perform secondary screening on the primary retrieval image based on the additional color set to obtain a secondary retrieval image, and classify the secondary retrieval image according to the additional color set, and each category corresponds to feature information;

[0037] A secondary retrieval processing module is used to stroke the intersection color features in the secondary retrieval image and the colors in the additional color set to obtain the retrieval outline of each color, and determine the number of color blocks corresponding to each color;

[0038] The image final retrieval module is used to calculate the similarity of the secondary retrieval image based on the number of color blocks and contour features, and output the final retrieval image according to the calculation results.

[0039] As a further solution of the present invention: the target image uploading module includes:

[0040] An image color recognition unit, used for recognizing the colors contained in the target image and obtaining a color set;

[0041] A contour feature determination unit, used for performing a stroke process on the edge of each color to obtain a contour feature of each color;

[0042] The feature information determination unit is used to determine the number of color blocks according to the number of contours in the contour feature of each color, and obtain feature information according to the color set, the contour feature and the number of color blocks.

[0043] As a further solution of the present invention: the image secondary retrieval module includes:

[0044] An additional color calling unit, used to call an additional color set corresponding to each feature information, wherein the additional color set includes zero, one or more additional colors;

[0045] A set descending order arrangement unit, used for arranging the additional color set in descending order according to the number of types of the additional colors;

[0046] A secondary screening image unit, used for performing secondary screening on the preliminary search image according to the descending order to obtain secondary search images, each of which corresponds to an additional color set;

[0047] The retrieval image classification unit is used to classify the secondary retrieval image according to the additional color set, and each category corresponds to an additional color set.

[0048] As a further solution of the present invention: the image final retrieval module includes:

[0049] A color block quantity screening unit, used to determine feature information corresponding to the secondary search image, and screen the secondary search image based on the number of color blocks of the feature information;

[0050] A contour similarity calculation unit, used to calculate the contour similarity between the retrieval contour of each color in the screened secondary retrieval image and the contour feature of each color in the feature information;

[0051] The calculation result determination unit is used to calculate the average value of the contour similarities of all colors to obtain the calculation result.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention performs feature recognition on each target image to obtain feature information, then performs intersection processing on the color sets of all target images to obtain intersection color features, and determines the additional color set corresponding to each feature information based on the intersection color features; then, based on the intersection color features, the images in the image library are preliminarily screened to obtain a preliminary retrieval image, and the preliminary retrieval image is secondary screened based on the additional color set to obtain a secondary retrieval image. So far, the present invention only uses color features for retrieval, which is efficient and fast. Then, the intersection color features in the secondary retrieval image and the colors in the additional color set are outlined to obtain the retrieval outline of each color, and the number of color blocks corresponding to each color is determined. The secondary retrieval image is similarity calculated based on the number of color blocks and the outline features, and the final retrieval image is output according to the calculation results. In this way, similarity calculation is only performed based on the intersection color features and the outlines of the colors in the additional color set, which not only reduces the amount of calculation, but also eliminates the interference of other colors, and introduces the number of color blocks, so that the retrieval results are more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 The figure is a flowchart of an image information retrieval method based on local matching.

[0055] Figure 2 The present invention is a flowchart for feature recognition of a target image in an image information retrieval method based on local matching.

[0056] Figure 3 The present invention is a flowchart of obtaining a secondary retrieval image in an image information retrieval method based on local matching.

[0057] Figure 4 The present invention is a flowchart of secondary screening of preliminary search images according to descending order in an image information retrieval method based on local matching.

[0058] Figure 5 The present invention is a flowchart for similarity calculation in an image information retrieval method based on local matching.

[0059] Figure 6 The present invention is a flowchart for screening secondary retrieval images in an image information retrieval method based on local matching.

[0060] Figure 7 A structural diagram of an image information retrieval system based on local matching. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0062] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0063] like Figure 1 As shown, an embodiment of the present invention provides an image information retrieval method based on local matching, the method comprising the following steps:

[0064] S100, receiving a plurality of target images at different angles, performing feature recognition on each target image, and obtaining feature information, wherein the feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to a number of color blocks;

[0065] S200, performing intersection processing on the color sets of all target images to obtain intersection color features, and determining an additional color set corresponding to each feature information based on the intersection color features;

[0066] S300, preliminarily screening images in an image library based on the intersection color feature to obtain a preliminary retrieval image;

[0067] S400, performing secondary screening on the preliminary search image based on the additional color set to obtain a secondary search image, and classifying the secondary search image according to the additional color set, each category corresponding to feature information;

[0068] S500, tracing the intersection color features in the secondary retrieval image and the colors in the additional color set to obtain a retrieval outline of each color, and determining the number of color blocks corresponding to each color;

[0069] S600, performing similarity calculation on the secondary retrieval image based on the number of color blocks and contour features, and outputting a final retrieval image according to the calculation result.

[0070] In the embodiment of the present invention, first, the user needs to upload several target images at different angles. Of course, the user can also upload only one target image. Then, the embodiment of the present invention will perform feature recognition on each target image. Feature recognition here is to simply identify the colors contained in the image to obtain feature information. The feature information includes a color set. Each color in the color set corresponds to a contour feature, and each color corresponds to a number of color blocks. For example, a certain color set is: red, blue and yellow, where the number of color blocks corresponding to red is four, and each target image corresponds to one feature information. Then, it is necessary to perform intersection processing on the color sets of all target images to obtain intersection color features. Based on the intersection color features, the additional color set corresponding to each feature information is determined. The additional color set is the set of color sets after removing the intersection color features. For example, if the color sets of all target images contain blue and yellow, then the intersection color features are blue and yellow. The additional color set of the color set of red, blue and yellow is red. Then, based on the intersection color feature, the images in the image library are preliminarily screened to obtain a preliminary search image, which contains all the colors in the intersection color feature; then, the preliminary search image is secondary screened based on the additional color set to obtain a secondary search image, which contains all the colors in a certain additional color set. So far, only the color feature is used for retrieval, which is efficient and fast. Then, the embodiment of the present invention will outline the intersection color feature in the secondary search image and the colors in the additional color set to obtain the search outline of each color, and determine the number of color blocks corresponding to each color, perform similarity calculation on the secondary search image based on the number of color blocks and the outline feature, and output the final search image according to the calculation result. In this way, only the similarity calculation is performed based on the intersection color feature and the outline of the color in the additional color set, which not only reduces the amount of calculation, but also eliminates the interference of other colors, and introduces the number of color blocks, so that the retrieval result is more accurate.

[0071] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of performing feature recognition on each target image to obtain feature information specifically includes:

[0072] S101, identifying colors contained in a target image to obtain a color set;

[0073] S102, performing a stroke process on the edge of each color to obtain a contour feature of each color;

[0074] S103, determining the number of color blocks according to the number of contours in the contour feature of each color, and obtaining feature information according to the color set, the contour feature, and the number of color blocks.

[0075] In an embodiment of the present invention, in order to determine the characteristic information, the colors contained in the target image are first identified to obtain a color set, and then the edges of each color are stroked, such as edge picking to obtain the contour features of each color, and the number of color blocks is determined according to the number of contours in the contour features of each color, so that the characteristic information of the target image is obtained.

[0076] like Figure 3 As shown, as a preferred embodiment of the present invention, the steps of performing secondary screening on the primary search image based on the additional color set to obtain the secondary search image and classifying the secondary search image according to the additional color set specifically include:

[0077] S401, retrieving an additional color set corresponding to each feature information, wherein the additional color set includes zero, one, or multiple additional colors;

[0078] S402, arranging the additional color set in descending order according to the number of types of the additional colors;

[0079] S403, performing secondary screening on the preliminary search images according to the descending order to obtain secondary search images, each of which corresponds to an additional color set;

[0080] S404, classifying the secondary retrieval image according to the additional color set, where each category corresponds to an additional color set.

[0081] In an embodiment of the present invention, before performing a secondary search, it is necessary to determine the additional color set corresponding to each feature information. It is easy to understand that the additional color set may contain zero, one or more additional colors, and then the additional color set is sorted in descending order according to the number of additional color types. Then, the preliminary search image is screened for the second time according to the descending order to obtain a secondary search image. Each secondary search image corresponds to an additional color set, which facilitates subsequent classification, that is, the secondary search image is classified according to the additional color set, and each category corresponds to an additional color set. In this way, the feature information corresponding to each secondary search image can be determined.

[0082] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of performing secondary screening on the preliminary search images according to the descending order to obtain the secondary search images specifically includes:

[0083] S4031, determining the additional color set arranged first according to the descending order;

[0084] S4032, performing secondary screening on the primary search image according to the additional colors in the additional color set to obtain a secondary search image corresponding to the additional color set;

[0085] S4033, removing the obtained secondary search image from the preliminary search image, and removing the extra color set from the descending order;

[0086] S4034, repeat steps S4031-S4033 until the secondary retrieval image is empty or the additional color set in descending order is empty.

[0087] In the embodiment of the present invention, when the secondary search is formally performed, the first additional color set is determined according to the descending order, and the primary search image is secondary screened according to the additional colors in the first additional color set to obtain a secondary search image corresponding to the additional color set; then the obtained secondary search image is removed from the primary search image, and the additional color set is removed from the descending order. Then the above search steps are repeated and looped until the secondary search image is empty or the additional color set in the descending order is empty, and the step is stopped.

[0088] like Figure 5 As shown in FIG. 1 , as a preferred embodiment of the present invention, the step of calculating the similarity of the secondary retrieval image based on the number of color blocks and the contour features specifically includes:

[0089] S601, determining feature information corresponding to the secondary search image, and screening the secondary search image based on the number of color blocks of the feature information;

[0090] S602, calculating the contour similarity between the search contour of each color in the filtered secondary search image and the contour feature of each color in the feature information;

[0091] S603, calculating the average value of the contour similarities of all colors to obtain a calculation result.

[0092] In an embodiment of the present invention, in order to further improve the retrieval efficiency and retrieval accuracy, the feature information corresponding to each secondary retrieval image is determined, the secondary retrieval image is screened based on the number of color blocks of the feature information, and then only the contour similarity between the retrieval contour of each color in the secondary retrieval image retained after screening and the contour feature of each color in the feature information is calculated. The contour similarity calculation can adopt methods such as Hausdorff distance and Fréchet distance, and a separate similarity calculation is performed for the contour of each color, eliminating interference from other factors as much as possible. For example, the retrieval contour includes three categories, namely, a red retrieval contour, a blue retrieval contour and a yellow retrieval contour, so that three contour similarities will be obtained. Finally, the average value of the contour similarities of the three colors is calculated to obtain a calculation result, and the final retrieval image is output according to the calculation result. For example, if the calculation result is higher than the set threshold, the corresponding secondary retrieval image will be regarded as the final retrieval image and thus output.

[0093] like Figure 6 As shown, as a preferred embodiment of the present invention, the step of screening the secondary search image based on the number of color blocks of the feature information specifically includes:

[0094] S6011, comparing the number of color blocks of each color in the feature information with the number of color blocks of the corresponding color in the secondary search image;

[0095] S6012: When the number of color blocks of any color in the feature information is greater than K×the number of color blocks of the corresponding color in the secondary search image, where K is a constant value greater than 1, the corresponding secondary search image is deleted.

[0096] In the embodiment of the present invention, it is easy to understand that the image finally retrieved needs to include the target image, and the retrieved image contains more elements. Therefore, the number of color blocks of a certain color in the retrieved image should be greater than the number of color blocks of the color in the target image. Based on this, the embodiment of the present invention will compare the number of color blocks of each color in the feature information with the number of color blocks of the corresponding color in the secondary retrieval image. When the number of color blocks of any color in the feature information is greater than K×the number of color blocks of the corresponding color in the secondary retrieval image, it is determined that the corresponding secondary retrieval image does not meet the requirements and is deleted.

[0097] like Figure 7 As shown, an embodiment of the present invention further provides an image information retrieval system based on local matching, the system comprising:

[0098] The target image uploading module 100 is used to receive a plurality of target images at different angles, perform feature recognition on each target image, and obtain feature information, wherein the feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to a number of color blocks;

[0099] The intersection color feature module 200 is used to perform intersection processing on the color sets of all target images to obtain intersection color features, and determine the additional color set corresponding to each feature information based on the intersection color features;

[0100] An image preliminary retrieval module 300 is used to perform preliminary screening of images in an image library based on the intersection color feature to obtain a preliminary retrieval image;

[0101] The image secondary retrieval module 400 is used to perform secondary screening on the primary retrieval image based on the additional color set to obtain a secondary retrieval image, and classify the secondary retrieval image according to the additional color set, each category corresponding to feature information;

[0102] The secondary search processing module 500 is used to stroke the intersection color features in the secondary search image and the colors in the additional color set to obtain the search outline of each color, and determine the number of color blocks corresponding to each color;

[0103] The image final retrieval module 600 is used to perform similarity calculation on the secondary retrieval image based on the number of color blocks and contour features, and output the final retrieval image according to the calculation result.

[0104] As a preferred embodiment of the present invention, the target image uploading module 100 includes:

[0105] An image color recognition unit, used for recognizing the colors contained in the target image and obtaining a color set;

[0106] A contour feature determination unit, used for performing a stroke process on the edge of each color to obtain a contour feature of each color;

[0107] The feature information determination unit is used to determine the number of color blocks according to the number of contours in the contour feature of each color, and obtain feature information according to the color set, the contour feature and the number of color blocks.

[0108] As a preferred embodiment of the present invention, the image secondary retrieval module 400 includes:

[0109] An additional color calling unit, used to call an additional color set corresponding to each feature information, wherein the additional color set includes zero, one or more additional colors;

[0110] A set descending order arrangement unit, used for arranging the additional color set in descending order according to the number of types of the additional colors;

[0111] A secondary screening image unit, used for performing secondary screening on the preliminary search image according to the descending order to obtain secondary search images, each of which corresponds to an additional color set;

[0112] The retrieval image classification unit is used to classify the secondary retrieval image according to the additional color set, and each category corresponds to an additional color set.

[0113] As a preferred embodiment of the present invention, the image final retrieval module 600 includes:

[0114] A color block quantity screening unit, used to determine feature information corresponding to the secondary search image, and screen the secondary search image based on the number of color blocks of the feature information;

[0115] A contour similarity calculation unit, used to calculate the contour similarity between the retrieval contour of each color in the screened secondary retrieval image and the contour feature of each color in the feature information;

[0116] The calculation result determination unit is used to calculate the average value of the contour similarities of all colors to obtain the calculation result.

[0117] The above only describes in detail the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0118] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0119] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0120] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. An image information retrieval method based on local matching, characterized in that: The method comprises the following steps: Receive a number of target images at different angles, perform feature recognition on each target image, and obtain feature information, wherein the feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to the number of color blocks; Perform intersection processing on the color sets of all target images to obtain intersection color features, and determine the additional color set corresponding to each feature information based on the intersection color features; Preliminarily screening images in the image library based on the intersection color feature to obtain a preliminary retrieval image; Perform secondary screening on the initial retrieval image based on the additional color set to obtain a secondary retrieval image, and classify the secondary retrieval image according to the additional color set, with each category corresponding to feature information; Stroke the intersection color features in the secondary retrieval image and the colors in the additional color set to obtain the retrieval outline of each color, and determine the number of color blocks corresponding to each color; The similarity of the secondary retrieval image is calculated based on the number of color blocks and contour features, and the final retrieval image is output according to the calculation results.

2. The image information retrieval method based on local matching according to claim 1, characterized in that: The step of performing feature recognition on each target image to obtain feature information specifically includes: Identify the colors contained in the target image and obtain a color set; Stroke the edge of each color to obtain the contour features of each color; The number of color blocks is determined according to the number of contours in the contour feature of each color, and feature information is obtained according to the color set, the contour feature, and the number of color blocks.

3. The image information retrieval method based on local matching according to claim 1, characterized in that: The steps of performing secondary screening on the primary search image based on the additional color set to obtain a secondary search image, and classifying the secondary search image according to the additional color set specifically include: Retrieve an additional color set corresponding to each feature information, where the additional color set includes zero, one, or multiple additional colors; Arrange the extra color set in descending order according to the number of extra color types; Perform secondary screening on the preliminary retrieval images according to the descending order to obtain secondary retrieval images, each of which corresponds to an additional color set; The secondary retrieval images are classified according to the additional color sets, where each category corresponds to an additional color set.

4. The image information retrieval method based on local matching according to claim 3, characterized in that: The step of performing secondary screening on the preliminary search images according to the descending order to obtain the secondary search images specifically includes: Determine the additional color set that is arranged first according to the descending order; performing a secondary screening on the preliminary search image according to the additional colors in the additional color set to obtain a secondary search image corresponding to the additional color set; Eliminating the obtained secondary retrieval image from the preliminary retrieval image, and excluding the extra color set from the descending order; Repeat the above three steps until the secondary retrieval image is empty or the additional color set in descending order is empty.

5. The image information retrieval method based on local matching according to claim 1, characterized in that: The step of calculating the similarity of the secondary retrieval image based on the number of color blocks and the contour features specifically includes: determining feature information corresponding to the secondary search image, and screening the secondary search image based on the number of color blocks of the feature information; Calculating the contour similarity between the retrieval contour of each color in the filtered secondary retrieval image and the contour feature of each color in the feature information; The average value of the contour similarities of all colors is calculated to obtain the calculation result.

6. The image information retrieval method based on local matching according to claim 5, characterized in that: The step of screening the secondary search image based on the number of color blocks in the feature information specifically includes: Comparing the number of color blocks of each color in the feature information with the number of color blocks of the corresponding color in the secondary retrieval image; When the number of color blocks of any color in the feature information is greater than K×the number of color blocks of the corresponding color in the secondary retrieval image, where K is a constant value greater than 1, the corresponding secondary retrieval image is deleted.

7. An image information retrieval system based on local matching, characterized in that: The system comprises: The target image uploading module is used to receive a number of target images at different angles, perform feature recognition on each target image, and obtain feature information. The feature information includes a color set, each color in the color set corresponds to a contour feature, and each color corresponds to the number of color blocks; The intersection color feature module is used to perform intersection processing on the color sets of all target images to obtain intersection color features, and determine the additional color set corresponding to each feature information based on the intersection color features; An image preliminary retrieval module is used to perform preliminary screening of images in the image library based on the intersection color feature to obtain a preliminary retrieval image; The image secondary retrieval module is used to perform secondary screening on the initial retrieval image based on the additional color set to obtain the secondary retrieval image, and classify the secondary retrieval image according to the additional color set, with each category corresponding to feature information; A secondary retrieval processing module is used to stroke the intersection color features in the secondary retrieval image and the colors in the additional color set to obtain the retrieval outline of each color and determine the number of color blocks corresponding to each color; The image final retrieval module is used to calculate the similarity of the secondary retrieval image based on the number of color blocks and contour features, and output the final retrieval image according to the calculation results.

8. The image information retrieval system based on local matching according to claim 7, characterized in that: The target image uploading module includes: An image color recognition unit is used to recognize the colors contained in the target image and obtain a color set; A contour feature determination unit, configured to perform a stroke process on the edge of each color to obtain a contour feature of each color; The feature information determining unit is used to determine the number of color blocks according to the number of contours in the contour feature of each color, and obtain feature information according to the color set, the contour feature and the number of color blocks.

9. The image information retrieval system based on local matching according to claim 7, characterized in that: The image secondary retrieval module includes: An additional color retrieving unit, configured to retrieve an additional color set corresponding to each feature information, wherein the additional color set includes zero, one, or multiple additional colors; A set descending order arrangement unit, used for arranging the additional color set in descending order according to the number of types of additional colors; a secondary screening image unit, configured to perform secondary screening on the preliminary search image according to a descending order to obtain secondary search images, each of which corresponds to an additional color set; The retrieval image classification unit is used to classify the secondary retrieval image according to the additional color set, where each category corresponds to an additional color set.

10. The image information retrieval system based on local matching according to claim 7, characterized in that: The image final retrieval module includes: a color block quantity screening unit, configured to determine feature information corresponding to the secondary search image, and screen the secondary search image based on the number of color blocks in the feature information; a contour similarity calculation unit, configured to calculate the contour similarity between the retrieval contour of each color in the filtered secondary retrieval image and the contour feature of each color in the feature information; The calculation result determination unit is used to calculate the average value of the contour similarities of all colors to obtain a calculation result.

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