Paper Info
Title
Face Recognition Based on Dual-Tree Complex Wavelet Transform under Low Illumination Environments
Abstract
Face recognition is quite challenging especially in a varying illumination scenario. In this paper, an effective method for face recognition based on dual-tree complex wavelet transform under low illumination environments is proposed. To alleviate the effect of lighting change on face image, logarithmic transform is performed, and a wavelet denoising model is then used to remove the low-frequency components in the details of LH, HL, and HH subbands. To enhance facial features, six difference images obtained from the four LL subbands are utilized and averaged to a so-called mean face. Results show that serious cast shadows on face images can be effectively removed such that face recognition rate can be greatly improved. To verify the feasibility of the proposed method, Yale face database B is used. Experimental results show that an overall recognition rate of 96% can be achieved.
Year
DOI
Venue
2014
10.1145/2683405.2683450
IVCNZ
Keywords
Field
DocType
feature measurement,algorithms,face recognition,denoising model,feature extraction,dual-tree complex wavelet transform
Computer vision,Facial recognition system,Pattern recognition,Effective method,Computer science,Dual tree,Feature extraction,Artificial intelligence,Logarithm,Complex wavelet transform,Wavelet denoising
Conference
Citations 
PageRank 
References 
0
0.34
20
Authors
4
Name
Order
Citations
PageRank
Deng-Yuan Huang116315.28
Shr-Huan Di200.34
Wu-Chih Hu324427.01
Yi-Jen Su401.35