Face authentication method and device

Abstract

The invention provides a face authentication method and device, and belongs to the field of image processing and pattern recognition. The method comprises the following steps: extracting Gabor texture features of an acquired face image sample pair through a Gabor filter, and separating real parts from virtual parts of the extracted Gabor texture features to obtain a plurality of feature graphs; summarizing the plurality of obtained feature graphs through an LBP (Local Binary Pattern) statistical histogram to serve as face feature expression of the face image pair; performing feature selection on the face feature expression of the face image sample pair through an AdaBoost (Adaptive Boosting) algorithm; and performing feature dimension reduction, feature judgment processing and the like on the face feature expression of the face image sample pair subjected to the feature selection through a PCA (Principal Components Analysis) algorithm and an LDA (Linear Discriminant Analysis) algorithm in sequence. Compared with the prior art, the face authentication method provided by the invention has the advantages of full extraction of sample texture information, low sample quantity demand, short algorithm time and low space complexity.

Description

technical field [0001] The invention relates to the fields of image processing and pattern recognition, in particular to a face authentication method and device. Background technique [0002] As the most effective document that can represent the identity of adults over 16 years old in China, the second-generation ID card records the holder's unique ID number, face image and other relevant information. However, the emergence of ID card theft, false ID cards, and multiple ID cards for one person has caused huge losses to many industries and countries. Therefore, using the second-generation ID card for identity authentication has become an important method to avoid the above phenomenon. This method is to compare the photo of the second-generation ID card with the face image collected on the spot to determine whether it is the same person. [0003] Due to the low resolution of the face image on the second-generation ID card, there is often a large age difference between the fac...

AI Technical Summary

Problems solved by technology

At present, ID card authentication methods in the prior art include methods based on eigenfaces and methods based on Gabor features, etc. However, for methods based on eigenfaces, the accuracy of face positioning is required to be high, and the method is not sensitive to occlusion, The change of posture is more sensitive, which can easily lead to inaccurate authentication; for the method based on Gabor features, more texture information of the image is required, and the number of samples required for training is larger, the corresponding time complexity is higher, and the dimension of the feature is obtained High, complex calculation, usually unable to meet real-time requirements

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