Method of Face Recognition Based on Red-Black Wavelet Transform and PCA

Authors:
Yuqing He;Huan He;Hongying Yang
Affiliations:
Department of Opto-Electronic Engineering, Beijing Institute of Technology, Beijing, 100081 P.R. China;Department of Opto-Electronic Engineering, Beijing Institute of Technology, Beijing, 100081 P.R. China;Department of Opto-Electronic Engineering, Beijing Institute of Technology, Beijing, 100081 P.R. China
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Year:
2008

Citing 3
Cited 0

Eigenfaces for recognition

Journal of Cognitive Neuroscience
Wavelet families of increasing order in arbitrary dimensions

IEEE Transactions on Image Processing
Face recognition using the nearest feature line method

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the development of the man-machine interface and the recognition technology, face recognition has became one of the most important research aspects in the biological features recognition domain. Nowadays, PCA(Principal Components Analysis) has applied in recognition based on many face database and achieved good results. However, PCA has its limitations: the large volume of computing and the low distinction ability. In view of these limitations, this paper puts forward a face recognition method based on red-black wavelet transform and PCA. The improved histogram equalization is used to realize image preprocessing in order to compensate the illumination. Then, appling the red-black wavelet sub-band which contains the information of the original image to extract the feature and do matching. Comparing with the traditional methods, this one has better recognition rate and can reduce the computational complexity.