Effective multiscale texture recognition method

A recognition method and multi-scale technology, applied in the field of pattern recognition, can solve the problems of conflicting evidence combination, fuzzy information processing and insufficient combination of related evidence

Inactive Publication Date: 2015-01-07
WUHAN UNIV
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Problems solved by technology

However, it has deficiencies in the combination of conflicting evidence, fuzzy information processing and related evidence combination.

Method used

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  • Effective multiscale texture recognition method
  • Effective multiscale texture recognition method
  • Effective multiscale texture recognition method

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Embodiment Construction

[0024] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only for illustration and explanation of the present invention, and are not intended to limit this invention.

[0025] This implementation adopts the current mainstream matlab tool programming. Among them, the calculation-intensive steps are mixed using matlab and c. please see figure 1 , the following are the specific steps of the embodiment of the present invention:

[0026] Step 1: Input the test image T;

[0027] Step 2: Calculate the image pyramid of the test image T, and the image pyramid iteratively filters the input image through a predefined low-pass filter; the specific implementation process is when the input test image T becomes the bottom layer or ...

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Abstract

The invention discloses an effective multiscale texture recognition method. The method comprises the steps that an image pyramid of an input image is calculated firstly, then an LBP operator is applied to the image pyramid with various scales, next, the image pyramid of each scale generates a feature vector, multiscale information is integrated through similarity fusion on each scale according to the D-S evidence principle, and particularly, the similarity of the tested image and a target sample is calculated by fusing the similarity between the tested image and the sample of each scale. By means of the effective multiscale texture recognition method, the identification precision of a public data set Brodatz'salbum and an MIT video texture database (VisTex) reaches 96.43% and 91.67%. Meanwhile, the method has a certain robustness to image rotation invariance and has a certain application value in the practical application.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and relates to a texture recognition method, in particular to an effective multi-scale texture recognition method. Background technique [0002] Image texture is an important visual means, and it is a ubiquitous and difficult-to-describe feature in images. Texture analysis technology has been an active research field in computer vision, image processing, image retrieval, etc. Texture analysis is one of the basic research fields of the above-mentioned applications, and its research contents mainly include: texture classification and segmentation, texture synthesis, texture retrieval and shape recovery from texture. One of the most basic problems of these research contents is texture feature extraction, texture microscopic heterogeneity, complexity, wide application and unclear concept bring great challenges to texture research. The goal of texture feature extraction is: the extracted...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06T7/44
Inventor 何发智孙俊陈晓
Owner WUHAN UNIV
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