期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2018
卷号：18
期号：3
页码：169-177
出版社：International Journal of Computer Science and Network Security
摘要：Face recognition system has been widely utilized for various sensitive applications such as Airport gates, special monitoring, and tracking system. The performance of most face recognition systems would significantly decrease if there were several variations in the illumination of dataset images. In this paper the proposed a new algorithm based on a combination of edge detection operators, features extractors and artificial neural network ANN as a classifier. The Second based on Laplacian comprise Zero cross, Laplacian of gaussian LOG, and Canny edge detection filters. A segmentation process is used to segment each image to equaled size blocks treats face edge pixels precisely. A new features extractor technique based on Linear Regression Slope SLP with discrete wavelet transformation (DWT) and principle components analysis PCA used for features extraction. ANN used for the data set classification and all results obtained evaluated. We tried a combination of various techniques like (Zero cross, DWT, SLP-PCA, ANN),(LOG, DWT, SLP-PCA, ANN),(Canny, DWT, SLP-PCA, ANN ). The proposed method is examined and evaluated with different face datasets using ANN classifier. The experimental results were displaying the superiority of the proposed algorithm over the algorithms that used the state-of-art techniques where the combinations (Zero cross, SLP, ANN) gained the best results and could outperform all the other algorithms.
关键词：Face Recognition; SLP; PCA; Neural Network; ANN
