vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff0d69060000003b0e000001000700 In this paper, we propose novel face recognition method based on local appearance feature extraction using hybrid mode of local ridge- let and fused dual-tree complex wavelet transform (DT-CWT). It provides a local multiscale description of images with good directional selectivity, effective edge representation and invariance to shifts and in-plane rotations. In the dual-tree implementation, two parallel dis- crete wavelet transform (DWT) with different lowpass and highpass filters in different scales are used. The linear combination of sub- bands generated by two parallel DWT is used to generate 6 different directional subbands with complex coefficients. It is insensitive to illumination variations and facial expression changes. 2-D dual-tree complex wavelet transform is less redundant and computationally efficient. The fusion of local DT-CWT coefficients of detail subbands and local Finite Ridgelet Transform (FRIT) coefficients of approxi- mate subbands of DT-CWT are used to extract the facial features which improve the face recognition with small sample size in less computation. The local features based methods have been success- fully applied to face recognition and achieved state-of-the-art per- formance. Normally most of the local appearance based methods the facial features are extracted from several local regions and concate- nated into an enhanced feature vector as a face descriptor. In this approach we divide the face into several (m×m) non-overlapped paral- lelogram blocks instead of square or rectangle blocks. The local mean and standard deviation of hybrid FRIT and fused DT-CWT coeffi- cients are used to describe the face image. Experiments, on two well- known databases, namely, Yale and ORL databases, shows the Local hybrid FRIT and fused DT-CWT approach performs well on illumi- nation, expression and perspective variant faces with single sample compared to PCA and global DT-CWT. Furthermore, in addition to the consistent and promising classification performances, our pro- posed Hybrid Local FRIT and fused DT-CWT based method has a really low computational complexity.
K. Jaya Priya1, R.S. Rajesh2
Mother Teresa Women's University1,Manonmaniam Sundaranar University2
Gabor Wavelet Transform, Finite Ridgelet Transform, Dual Tree Discrete Wavelet Transform, Dual Tree Complex Wavelet Transform, PCA, Parallelogram Regions
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 1 , Issue: 4 , Pages: 186-191 )
Date of Publication :
May 2011
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