Literature Survey on Development of An Algorithm for Face Recognition using Wavelet Neural Network
Priyanka Dharane1, A. S. Vibhute2
1Miss. Priyanka Dharane, Department of E&TC, BMIT Solapur, University, Solapur (Maharashtra), India.
2Prof. A. S. Vibhute, Department of E&TC, BMIT Solapur, University, Solapur (Maharashtra), India.
Manuscript received on 10 December 2014 | Revised Manuscript received on 20 December 2014 | Manuscript Published on 30 December 2014 | PP: 163-168 | Volume-4 Issue-7, December 2014 | Retrieval Number: G1929124714/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Automatic face recognition system is an important component of intelligent human computer interaction systems for biometric. It is an attractive biometric approach, to distinguish one person from another. To perform Automatic face recognition system, the hybrid approach Wavelets face detection and Neural Network based Face Recognition is used. The face recognition accuracy is can be increased using a combination of Wavelet, PCA, and Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. For preprocessing and feature extraction steps, we apply a combination of wavelet transform and PCA. During the classification stage, the Neural Network (MLP) is explored to achieve a robust decision in presence of wide facial variations.
Keywords: Face Detection, Neural Network, PCA, Face Recognition, Wavelet.
Scope of the Article: Heterogeneous Wireless Networks