The cortex transform: rapid computation of simulated neural images
Computer Vision, Graphics, and Image Processing
Machine Learning
Signal Processing - Image and Video Coding beyond Standards
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A Multiscale and Multidirectional Image Denoising Algorithm Based on Contourlet Transform
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
Shiftable multiscale transforms
IEEE Transactions on Information Theory - Part 2
The finite ridgelet transform for image representation
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Curvelet based face recognition via dimension reduction
Signal Processing
Novel face recognition approach based on steerable pyramid feature extraction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Face recognition using curvelet transform
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Robust face recognition using curvelet transform
Proceedings of the 2011 International Conference on Communication, Computing & Security
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This paper proposes a new method for face recognition based on a multiresolution analysis tool called Digital Curvelet Transform. Multiresolution ideas notably the wavelet transform have been profusely employed for addressing the problem of face recognition. However, theoretical studies indicate, digital curvelet transform to be an even better method than wavelets. In this paper, the feature extraction has been done by taking the curvelet transforms of each of the original image and its quantized 4 bit and 2 bit representations. The curvelet coefficients thus obtained act as the feature set for classification. These three sets of coefficients from the three different versions of images are then used to train three Support Vector Machines. During testing, the results of the three SVMs are fused to determine the final classification. The experiments were carried out on three well known databases, viz., the Georgia Tech Face Database, AT&T "The Database of Faces" and the Essex Grimace Face Database.