Texture description method and system based on improved local binary pattern

Abstract

The invention discloses a texture description method and system based on an improved local binary pattern. According to the invention, on one hand, the method includes extracting all equivalent modesin an original image; extracting all non-equivalent modes in the original image at the same time, taking a part of non-equivalent modes with high occurrence frequency from the non-equivalent modes asdominant non-equivalent modes based on the occurrence frequency of each type of non-equivalent modes, and constructing a mixed mode by utilizing all the equivalent modes and all the non-equivalent modes; on the other hand, the method includes selecting a rotary encoder or a natural encoder for hybrid encoding according to the image noise condition, and when the image is in a normal state, selecting the rotary encoder; and when the image is in a light alarm state, selecting a natural encoder. According to the method, texture description information in a non-equivalent mode is mined, the problemthat the texture description capability is reduced after a traditional LBP ignores the non-equivalent mode is solved, meanwhile, two coding modes which are freely switched according to the image noise degree are provided, and the anti-noise performance of the texture description process is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a texture description method and system based on an improved local binary mode. Background technique [0002] How to efficiently extract texture features that are low-dimensional, sparse, noise-robust, and adaptable to changing illumination to achieve high-performance object recognition or image classification has always been a hot issue in the field of image processing. Local Binary Patterns (LBP) is a local feature of the pixel layer, which encodes the relative gray value between the central pixel and the neighboring pixels. Because of its simple theory, efficient calculation, strong feature discrimination and low computational complexity, it is widely used in texture classification, face recognition, image retrieval, face detection and facial expression analysis and other fields. The texture analysis method based on LBP has become one of the advanced text...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a texture description method and system based on the improved local binary mode, which overcomes the problems of the traditional LBP ignoring the non-equivalent mode, the decline of the texture analysis ability and the edge description ability and the sensitivity to noise, and innovatively excavates The texture description information in th

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