Face recognition method based on multi-resolution multi-threshold local binary pattern

A local binary pattern and face recognition technology, applied in the field of pattern recognition, can solve problems such as difficulty in obtaining the spatial structure information of faces and being easily affected by noise
CN103778434AInactive Publication Date: 2014-05-07CHONGQING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
CHONGQING UNIV OF POSTS & TELECOMM
Publication Date
2014-05-07
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a face recognition method based on the multi-resolution multi-threshold local binary pattern, and pertains to the technical field of pattern recognition. Through the local binary pattern, spatial structure information of positions of face facial organs is hard to acquire, and at the same time, the LBP operator adopts size relationship between local region neighbour pixels and the central pixel to perform encoding, so the noise effect exists; in order to solve the problems, the method adopts different thresholds to perform LBP image encoding, and finally, face local and overall information is acquired through different division methods, so the MRTLBP characteristic information extraction is more discriminative. The characteristics are used as the face discrimination characteristics for classification and recognition. Classification and recognition are performed by adopting nearest neighbor classification devices. The experimental analysis shows that the method of the invention has good face characteristic expressing capability and has high robustness for illumination, expressions and poses.
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Description

technical field

[0001] The invention relates to the technical field of pattern recognition, in particular to a face recognition method based on a multi-resolution multi-threshold local binary pattern (LBP). Background technique

[0002] Face recognition is a typical research topic in the fields of pattern recognition, image analysis and understanding, etc. It not only has important theoretical value, but also has important application prospects in security, financial and other fields, so it has been widely received in academia and industry. At present, some practical commercial systems have emerged. However, due to changes in the image acquisition conditions and the attributes of the face itself, the appearance of different photos of the same person may vary greatly, which increases the difficulty of recognition. Therefore, improving the robustness of face recognition systems to these changes has become one of the important goals of researchers in this field.

[0003] Wave...

Claims

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