A Novel Way of Face Recogniton to Improve the Quality of Features Eztraction
This paper sets to improve the representative information of the eigenvector of the face in which Haar wavelet is applied to decompose the face. The high-frequency of the face decomposed on 1 scale is preserved as a high-frequency feature-vector (HF), and the low-frequency of the face decomposition is applied for dimension reduced by Fishers linear discriminant(FLD). Then we combined the highfrequency feature-vector and the eigenvector extracted by FLD as a stand-by recognition face eigenvector(SRFE). The data of the SRFE is used to train and to test a fuzzy neural network which is applied for face recognition. A simulation of the proposed algorithm is done on the basis of Olivetti Research Lab(ORL) face database, and the results show that the algorithm is able to recognize quickly with high recognition rate.
face recognition Haar wavelet transform Fishers linear discriminant fuzzy neural network
Rong Hu Jianping Wang Weihong Xu Jiaying Wu
School of Computer Science and Engineering.Nanjing University of Science and Technology.Changsha Aer Changsha Aeronautical Vocational and Technical College Changsha,China College of Computer and Communications Engineering.Changsha University of Science &Technology,Changs School of Computer Science and Engineering.Nanjing university of Science and Technology Nanjing,Chin
国际会议
上海
英文
2766-2770
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）