Face identification algorithm under different illumination conditions

Abstract

The invention discloses a face identification algorithm under different illumination conditions, comprises the steps that: (1) the inputted face original image F(x, y) is subjected to Gaussian filter so as to eliminate noise point in the image and smooth the image, thereby obtaining a new image F'(x, y); (2) the F' (x, y) is subjected to feature extraction by using a Weber local operator description; (3) an edge is extracted from a new image WF(x, y) by LoG operator operation; (4) the inputted image is converted to a principal component space by using fast PCA algorithm; (5) in the PCA transform space, a inter-class scatter matrix is calculated (img file='DDA0000447013750000011.TIF' wi ='45' he='65' / ); (6) the obtained new image feature WF'(x, y) is projected on a feature projection vector group Phi; (7) finally, a nearest neighbor classifier carries out classification. The invention carries out feature extraction of the image operated by the LoG operator, more complete identification information of the original imagely can be extracted, the data from the above experiment shows that the new algorithm can obtain the prominent face identification rate from all three face databases, and also completely meet the real-time requirements in the speed.

Description

Technical field [0001] The present invention relates to the technical field of face recognition, in particular to a face recognition algorithm under changing lighting conditions. Background technique [0002] Face recognition is an important research topic in the current field of pattern recognition and artificial intelligence. In the past two decades, the research of face recognition technology has become a very active research direction. Because of its direct, friendly, convenient, and easy to accept for users, the current face recognition technology has been widely used in document verification, video Surveillance, entrance control, criminal investigation and solving cases. However, there are still many problems in face recognition technology that have not been well resolved. At present, practical face recognition systems basically require the recognized person to be in a very fixed environment (such as fixed lighting, etc.) and be very cooperative ( If there is no expressio...

AI Technical Summary

Problems solved by technology

The third category is the face modeling method. This type of method requires known lighting conditions or known object shape and reflection characteristics. Its assumptions are too many and too strong, which limits its practical application.

However, in the process of face recognition, the above method will inevitably be affected by illumination changes, resulting in shadowed or overbright areas in the face area, affecting subsequent feature extraction and resulting in a decline in recognition rate

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