Automatic recognition of human faces is a significant problem in the development and application of pattern recognition. In this paper, we introduce a simple technique for identification of human faces in cluttered scenes based on neural nets. In detection phase, neural nets are used to test whether a window of 18x27 pixels contains a face or not. A major difficulty in learning process comes from the large database required for face / nonface images. We solve this problem by dividing these data into two groups. Such division results in reduction of computational complexity and thus decreasing the time and memory needed during the test of an image. The proposed face recognition technique consists of three parts; preprocessing, feature extraction, and recognition steps. Gradient Vector method is used for facial feature extraction. A face recognition system based on recent method which concerned with both representation and recognition using artificial neural networks is presented. It then evaluates the performance of the system by applying two photometric normalization techniques: histogram equalization and homomorphic filtering. The system produces promising results for face verification and face recognition. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org
[1]
Yongsheng Gao,et al.
Face Recognition Using Line Edge Map
,
2002,
IEEE Trans. Pattern Anal. Mach. Intell..
[2]
M. Grgic,et al.
Sub-Image Homomorphic Filtering Technique for Improving Facial Identification under Difficult Illumination Conditions
,
2006
.
[3]
Achim Sanjay Manikarnika.
A General Face Recognition System
,
2006
.
[4]
Patrick J. Flynn,et al.
Overview of the face recognition grand challenge
,
2005,
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[5]
Andy Adler,et al.
Comparing Human and Automatic Face Recognition Performance
,
2007,
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[6]
Marco Furini,et al.
International Journal of Computer and Applications
,
2010
.
[7]
S.A. Nazeer,et al.
Face Recognition System using Artificial Neural Networks Approach
,
2007,
2007 International Conference on Signal Processing, Communications and Networking.