Human face recognition method based on local feature learning

A face recognition and local feature technology, applied in the field of biometrics, can solve the problems of unsatisfactory face recognition effect with changes in expression and large differences in illumination brightness, and achieve high recognition rate, good robustness, and improved face recognition performance. Effect

Inactive Publication Date: 2011-08-17
MYDIGITHAT TECH
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Problems solved by technology

[0004] Traditional face recognition methods based on local feature learning can achieve certain recognition results, but t...

Method used

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  • Human face recognition method based on local feature learning
  • Human face recognition method based on local feature learning
  • Human face recognition method based on local feature learning

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Embodiment Construction

[0021] In order to facilitate the understanding of the technical solutions of the present invention, the following will be introduced in conjunction with specific implementation manners. like figure 1 As shown, a face recognition method based on local feature learning, the method includes two steps of establishing a training model and a recognition model, wherein the establishment of a training model includes the following steps: (a) performing the known face sample classification Block processing, and calculate the face sample data of each block through the LBP operator and LTP operator, to obtain the local histogram vector of each face sample data; (b) for the same person in all face samples The chi-square histogram distance calculation is performed on the local histogram vectors of the same position on any two different face samples to obtain the positive sample feature library; (c) on any two face samples of different people in all face samples The chi-square histogram di...

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Abstract

The invention discloses a human face recognition method based on local feature learning, which comprises the following steps of: (a) partitioning a known classified human face sample into blocks, and calculating data of the human face sample of each block through an LBP (Length Between Perpendiculars) operator and an LTP (Long-Term Potentiation) operator to obtain a local histogram vector a of data of the human face sample of each block; (b) performing chi-square histogram distance calculation on local histogram vectors of the same positions on any two different human face samples of the same person in all human face samples to obtain a positive sample feature library; and (c) performing chi-square histogram distance calculation on local histogram vectors of the same positions on any two human face samples of different persons in all human face samples to obtain a negative sample feature library. The human face recognition method based on the local feature learning, provided by the invention, has the advantages of quick response, high accuracy and good recognition effect.

Description

technical field [0001] The invention relates to a biological recognition technology, in particular to a face recognition method based on local feature learning. Background technique [0002] Biometric identification technology refers to the technology that uses the inherent physiological or behavioral characteristics of living organisms (mainly referring to people) for identification. Compared with traditional identification technologies such as documents, magnetic cards, passwords, etc., biometric identification technology makes full use of the inherent biological characteristics of individuals, prevents identity forgery and theft from the source, and is more effective, reliable, and safe. The system has been more and more widely used. [0003] In biometric identification technology, compared with iris recognition, fingerprint recognition, etc., face recognition has the advantages of naturalness, directness, friendliness and non-contact, and is highly favored by people. It...

Claims

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Application Information

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IPC IPC(8): G06K9/66
Inventor 吴希贤
Owner MYDIGITHAT TECH
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