DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLNE-523

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-2,Issue-3  ( Mar, 2014 )
Paper Title
AN EFFICIENT FACE RECOGNITION USING DCT, ADAPTIVE LBP AND GABOR FILTER WITH SINGLE SAMPLE PER CLASS
Author Name
DIVYA PAUL, A.USHA RUBY, J.GEORGE CHELLIN CHANDRAN
Affilition
Department of Computer Science and Engineering, CSI College of Engineering Research Scholar, Bharath University
Pages
53-55
Abstract
Nowadays face recognition plays an important role in today’s world. It has achieved greater importance in the field of information security, law enforcement and surveillance. Now this face recognition approach is applied to many areas like Airport security, Driver’s License, Passport, Customs and Immigration. In face recognition Local appearance based methods had achieved greater performance. In this paper we have proposed single sample per class using Discrete Cosine Transform, Adaptive Local Binary Pattern and Gabor Filter based on local selective feature extraction approach. Discrete Cosine Transform is used to extract the facial features from the face image .It helps to extract the facial features efficiently. Then the Gabor filter extracts the textual feature and generates a binary face template based on that features. And this binary face template act like a mask to extract local texture information using Adaptive Local binary pattern. Adaptive Local binary pattern method is efficient to face recognition since it is less sensitive to illumination and scaling. And this approach uses histogram-based matching. It reduces the computational time complexity and space complexity. Here FERET database is used for face recognition.
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