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Image texture classification method based on Weber local binary counting

A local binary, image texture technology, applied in computing, computer parts, instruments, etc., can solve the problems of time-consuming processing of pictures, large feature dimensions, low classification accuracy, etc., and achieve good advantages and feature dimensions. Small, the effect of guaranteeing the classification performance

Inactive Publication Date: 2017-02-01
郑州新马科技有限公司
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide an image texture classification method based on Weber local binary counting, which is used to overcome the problems of low classification accuracy, large feature dimension and time-consuming processing of pictures in existing classification methods

Method used

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  • Image texture classification method based on Weber local binary counting
  • Image texture classification method based on Weber local binary counting
  • Image texture classification method based on Weber local binary counting

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specific Embodiment approach

[0046] Step 1. Multi-scale decomposition of the texture image, the specific process is:

[0047] (1) Taking each pixel as the center, divide the texture image into blocks;

[0048] (2) Calculate the difference between the center pixel and its neighbor pixels;

[0049] (3) Calculate the differential excitation and local binary counting modes;

[0050] (4) Construct all L Differential excitation distribution and local binary counting mode distribution at a scale;

[0051] Step 2. Construct differential excitation vector features and local binary count histogram features. The specific process is:

[0052] (1) Use the local binary counting pattern as an adaptive threshold to divide the differential excitation distribution;

[0053] (2) Calculate the differential excitation vector features;

[0054] (3) Calculate local binary count histogram features;

[0055] Step 3. Construction L The scaled Weber local binary counting descriptor feature, the specific process is:

[0056...

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Abstract

The invention discloses an image texture classification method based on Weber local binary counting. Multi-scale decomposition is firstly carried out on a texture image, and a differential excitation vector characteristic and a local binary counting histogram characteristic are built; L scales of Weber local binary counting descriptor characteristics are then built; and finally, a K nearest neighbor classifier is adopted to classify the extracted L scales of Weber local binary counting characteristics for the texture image, and a classification result is acquired. The method of the invention has the beneficial effects of effectively improving the texture image classification precision, effectively being adaptive to changes of a texture image imaging condition and effectively improving the classification speed.

Description

technical field [0001] The invention relates to texture image classification in the fields of pattern recognition and computer vision, in particular to an image texture classification method based on Weber local binary counting. Background technique [0002] Texture exists widely in the objective world. It is a basic attribute to express the surface or structure of objects, and it is also a very important research direction in computer vision. The intuitive meaning of texture is very clear. But people still have a vague idea of ​​what texture is. In graphics processing, texture has a broad and general meaning. Texture-based analysis and applied research has been conducted for nearly six decades. The research on texture is still very active. Many research institutions at home and abroad are engaged in this work. In recent years, in internationally renowned magazines and important conferences, research results on texture recognition emerge in endlessly, as many as hundreds ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/467G06V10/50G06F18/24147
Inventor 董永生冯金旺郑林涛梁灵飞王晓红普杰信
Owner 郑州新马科技有限公司
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