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M. S. Thirumalai
Publisher: M.S. Thirumalai
11249 Oregon Circle
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Efficient Face Recognition Method for
Karthick K., M.E.
Sughapriya N., M.E. Student
In this paper, we propose efficient methods for face recognition which provides better performance for given images which might be taken in presence of different lighting conditions and slight pose variations. Face detection is performed through segmentation and face region coordinate computation. In face recognition process for each training sample the distance metric is learned to find the similarities between images. In order to raise the efficiency of face recognition, a method based on distance metric learning and hybrid neural network (back-propagation (BP) neural network and probabilistic neural network (PNN) integration) was introduced. This method based on FFT in feature extraction, distance metric data is propagated into the HNN and outputs the classification and recognition results by relative voting method. The performance analysis comparison proves the superiority of the proposed method.
Keywords: Face detection, face recognition, distance learnng,hybrid neural network.
Face recognition can be categorized into two classes: face verification and face identification. The first aims to verify whether a given pair of face images/video is from the same person or not, and the second aims to recognize the given face image from a gallery set and find the most matched one. In this work, we focus on face detection and identification, which aims to determine whether a given pair of face images captured in unconstrained environments is from the same person or not. Images containing faces are essential to intelligent vision-based human computer interaction, person identification and verification.
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Karthick K., M.E.
Sughapriya N, M.E. Student
Department of Electronics & Communication Engineering
Sri Subramanya College of Engineering & Technology
NH - 209, Sukkamanaickenpatti