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An Efficient Face Recognition Using Multi-Kernel Based Scale Invariant Feature Transform
CH. Hima Bindu, K. Manjunathachari
Pages - 39 - 47     |    Revised - 31-05-2018     |    Published - 30-06-2018
Volume - 12   Issue - 2    |    Publication Date - June 2018  Table of Contents
SIFT, SVM, Multi-kernel SIFT, Face Recognition.
Face recognition has gained significant attention in research community due to its wide range of commercial and law enforcement applications. Due to the developments in the past few decades, in the current scenario, face recognition is employing advanced feature identification techniques and matching methods. In spite of vast research done, face recognition still remains an open problem due to the challenges posed by illumination, occlusions, pose variation, scaling, etc. This paper is aimed at proposing a face recognition technique with high accuracy. It focuses on face recognition based on improved SIFT algorithm. In the proposed approach, the face features are extracted using a novel multi-kernel function (MKF) based SIFT technique. The classification is done using SVM classifier. Experimental results shows the superiority of the proposed algorithm over the SIFT technique. Evaluation of the proposed approach is done on CVL face database and experimental results shows that the proposed approach has a recognition rate of 99%.
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Mrs. CH. Hima Bindu
Dept. of ECE, GITAM University, Hyderabad, INDIA - India
Mr. K. Manjunathachari
Dept. of ECE GITAM University Hyderabad, INDIA - India