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Cross-channel local binary pattern color texture classification method

A local binary pattern, texture classification technology, applied in character and pattern recognition, computer parts, instruments, etc., can solve the problem of inability to effectively utilize color channel dependencies and correlations, and the inability of traditional local binary patterns to extract color information, etc. question

Active Publication Date: 2021-03-16
苏州三润精密电子科技有限公司
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  • Application Information

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a color texture classification method of cross-channel local binary mode, which is used to solve the problem that the traditional local binary mode (LBP) and its extended algorithm cannot extract color information and cannot effectively use the color between color channels. Dependencies and correlations and other issues

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  • Cross-channel local binary pattern color texture classification method
  • Cross-channel local binary pattern color texture classification method

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Embodiment

[0033] A color texture classification method for cross-channel local binary patterns, comprising the following steps:

[0034] Step 1: Separate and arrange the color texture image into a cube in the order of R-G-B channels;

[0035] Step 2: Use a local cube as a model to sample sequentially from local to global;

[0036] Step 3: Divide each local cube into 3 orthogonal faces;

[0037] Step 4: extract multi-channel local binary mode MCLBP descriptors from three orthogonal surfaces, and construct joint vectors;

[0038] Step 5: Rotate the order of channels, repeat steps 1 to 4 to obtain the other two joint vectors, normalize and concatenate to obtain the final color image feature histogram, and use chi-square distance and nearest neighbor classifier for classification.

[0039] In this embodiment, in step 1, the color texture image is separated and arranged in a cube in the order of R-G-B channels, that is, a color texture image with a size of M×N is separated from its color c...

specific Embodiment approach

[0058] (1) Color space selection: In addition to the RGB space, there are some other commonly used digital image color spaces, such as HSV, YCbCr, and L*a*b. Extensive experiments on 4 standard databases show that different color spaces affect the classification performance of texture images. The multi-scale classification results are shown in Table 1. It can be seen from Table 1 that the MCLBP method proposed in this paper can achieve satisfactory and stable classification accuracy in different scales and different color spaces. However, MCLBP has a more stable effect in the RGB color space and generally has higher classification accuracy than in other color spaces.

[0059] Table 1

[0060]

[0061] (2) Compare this method with other 12 texture feature extraction methods, the results are shown in Table 2;

[0062] Through comparison with other methods, it can be verified that the method proposed in the present invention has good advantages over other 12 methods: effect...

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Abstract

The invention relates to the technical field of image processing and pattern recognition, in particular to a cross-channel local binary pattern color texture classification method. The method comprises the following steps: 1, separating color texture images according to an RGB channel sequence and arranging the color texture images into a cube; 2, sequentially sampling from local expansion to global expansion by taking a local cube as a model; 3, dividing each local cube into three orthogonal surfaces; 4, extracting a multi-channel local binary pattern MCLBP descriptor from the three orthogonal surfaces, and constructing a joint vector; 5, turning the channel sequence, repeating the steps 1 to 4 to obtain another two joint vectors, normalizing and cascading to obtain a final color image feature histogram, and classifying by adopting chi-square distance and a nearest neighbor classifier.

Description

technical field [0001] The invention relates to the technical field of image processing and pattern recognition, in particular to a color texture classification method of cross-channel local binary patterns. Background technique [0002] Texture analysis is one of the research hotspots in the field of pattern recognition and computer vision. Specifically, texture description and classification play a key role in many computer vision applications. Therefore, how to effectively obtain representative texture features is the key to image analysis and understanding. [0003] At present, grayscale texture analysis technology is becoming more and more mature, and many grayscale texture descriptors have been developed and successfully applied to many fields of image classification. However, since most techniques only texture-classify grayscale images, color information is discarded from it, which is an important cue for visual perception. How to make full use of color information...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/467G06V10/50G06F18/2413G06F18/24147
Inventor 束鑫宋志刚石亮范燕黄树成
Owner 苏州三润精密电子科技有限公司
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