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Face Recognition by Using Back Propagation Artificial Neural Network and Windowing Method

Mehmet Korkmaz and Nihat Yilmaz
Department of Electrical and Electronics Engineering, Selcuk University, Konya, Turkey

Abstract—Biometric recognition have been getting popular in recent years. In this paper one of the biometric recognition techniques, face recognition, is purposed by using windowing feature extraction method and artificial neural network classifier. In the paper, ORL database which consist of ten images of forty people is used to test our software and method. First of all, images are separated to the different size windows, 4 by 4 and 8 by 8. Then, it is obtained the means of each window and totally sixteen by one and sixty four by one vectors features are obtained, respectively. According to the created features of each images, Artificial Neural Network (ANN) is trained by using different learning rate, momentum factor etc. Finally, the network is tested as to testing values and it’s observed the remarkable results of the study. As it expected, the methods which separate the images 8 by 8 is more successful than the other one. On the other hand, 4 by 4 windowing feature have also remarkable results, although it has less features.

Index Terms—artificial neural network, biometric recognition, face recognition, feature extraction

Cite: Mehmet Korkmaz and Nihat Yilmaz, "Face Recognition by Using Back Propagation Artificial Neural Network and Windowing Method," Journal of Image and Graphics, Vol. 4, No. 1, pp. 15-19, June 2016. doi: 10.18178/joig.4.1.15-19