Title :
Local Statistical Features of Dual Tree Complex Wavelet Transform on Parallelogram Image Structure for Face Recognition with Single Sample
Author :
Priya, K. Jaya ; Rajesh, R.S.
Author_Institution :
Dept. of Comput. Sci., Mother Teresa Women´´s Univ., Kodaikanal, India
Abstract :
In this paper, we propose a novel face recognition method based on local appearance feature extraction using dual-tree complex wavelet transform (DT-CWT). It provides a local multiscale description of images with good directional selectivity and invariance to shifts and in-plane rotations. In the dual-tree implementation, two parallel discrete wavelet transform (DWT) with different lowpass and highpass filters in different scales were used. The linear combination of subbands 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 local DT-CWT coefficients 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 successfully applied to face recognition and achieved state-of-the-art performance. Normally most of the local appearance based methods the facial features are extracted from several local regions and concatenated into an enhanced feature vector as a face descriptor. In this approach we divide the face into several (m ? m) non-overlapped parallelogram blocks instead of square or rectangle blocks. The local mean, standard deviation and energy of complex wavelet coefficients are used to describe the face image. Experiments, on two well-known databases, namely, Yale and ORL databases, shows the Local DT-CWT approach performs well on illumination, 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 proposed Local DT-CWT based method has a really low computational complexity.
Keywords :
computational complexity; discrete wavelet transforms; face recognition; feature extraction; image enhancement; ORL databases; Yale databases; computational complexity; discrete wavelet transform; dual tree complex wavelet transform; face descriptor; face recognition method; feature vector enhancement; highpass filters; local appearance feature extraction; local features based methods; local statistical features; lowpass filters; parallelogram image structure; Concatenated codes; Discrete wavelet transforms; Face recognition; Facial features; Feature extraction; Filters; Image databases; Lighting; Wavelet coefficients; Wavelet transforms; Dual tree complex wavelet transform; Dual tree discrete wavelet transform; Face recognition; Gabor wavelet transform; PCA; Parallelogram regions;
Conference_Titel :
Recent Trends in Information, Telecommunication and Computing (ITC), 2010 International Conference on
Conference_Location :
Kochi, Kerala
Print_ISBN :
978-1-4244-5956-8
DOI :
10.1109/ITC.2010.63