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Independent Component Analysis of Edge Information for Face Recognition
Kailash Jagannath Karande, Sanjay N Talbar
Pages - 120 - 130     |    Revised - 05-08-2009     |    Published - 01-09-2009
Volume - 3   Issue - 3    |    Publication Date - June 2009  Table of Contents
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KEYWORDS
Principle Component analysis (PCA),, Independent Component Analysis (ICA), Laplacian of Gaussian ( LoG, Canny edge detection, Euclidean distance classifier, Mahalanobis distance classifier.
ABSTRACT
In this paper we address the problem of face recognition using edge information as independent components. The edge information is obtained by using Laplacian of Gaussian (LoG) and Canny edge detection methods then preprocessing is done by using Principle Component analysis (PCA) before applying the Independent Component Analysis (ICA) algorithm for training of images. The independent components obtained by ICA algorithm are used as feature vectors for classification. The Euclidean distance and Mahalanobis distance classifiers are used for testing of images. The algorithm is tested on two different databases of face images for variation in illumination and facial poses up to 180 degree rotation angle.
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Professor Kailash Jagannath Karande
Sinhgad Institute of Technology, Lonavala - India
kailashkarande@yahoo.co.in
Dr. Sanjay N Talbar
SGGS IET Nanded - India