Keywords : Face recognition


Face Recognition using Artificial Intelligent Techniques

Laheeb Mohammad Ibrahim; Ibrahim A. Saleh

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 2, Pages 211-227
DOI: 10.33899/csmj.2009.163809

Face recognition is considered one of the visual tasks which humans can do almost effortlessly while for computers it is a difficult and challenging task. This research deals with the problem of face recognition. A novel approach is presented for both face feature extraction and recognition, first, we introduce Principal Component Analysis (PCA) for face feature extraction, Generalized Regression Artificial Neural network for face recognition. The performance of the whole system was done after training with 120 color images (40 human faces with 3 poses) and testing using 40 color images. The images were taken from Collection of Facial Images: Faces95 by Computer Vision Science Research Projects. Experimental results for proposed human face recognition confirm that the proposed method lends itself to good extraction and classification accuracy relative to existing techniques.
 

Principle Component Selection for Face Recognition Using Neural Network

Ibrahim A. Saleh

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 1, Pages 179-191
DOI: 10.33899/csmj.2009.163777

Face Recognition is an emerging field of research with many challenges such as large set of images,. Artificial Neural Network approach is one of the simplest and most efficient method to overcome these obstacles in developing a system for Face Recognition.. This research deals with both face extraction and recognition, Firstly, Eigenfaces are eigenvectors of covariance matrix, representing given image space. Any new face image can then be  represented as a linear combination of these Eigenfaces which can be found  by Principal Component Analysis (PCA) for face extraction,and by Recurrent (Time Cycling) Back Propagation artificial neural network for face recognition. The whole system was performed by training using 120 color images (40 human faces with 3 poses) and testing using 40 color images. The images were taken from Collection of Facial Images: Faces95 by Computer Vision Science Research Projects. The results indicated  that the proposed method lends itself to good extraction and classification accuracy relative to existing techniques.
 

Face Recognition and Determination in Color Images

Manar Younis Kashmola; Najim Abdallah Altahhan

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 1, Pages 13-29
DOI: 10.33899/csmj.2009.163782

The aim of this study is face detection in colored images (single or multiple faces) where an algorithm based on skin color information, in addition to face features like eyes and mouth, are used. The study deals with the effect of colored images type in test where (jpg, jpeg) images are used. Different images of persons were obtained from the internet and different images background and their effect on face detection within the image are studied. Two groups of colored images, photographic images taken by a photographic camera and digital images taken by a digital camera are also studied. A comparison between the results of the two groups concerning face detection is made. This comparison is based on the face orientation angle for each image in the two groups using the frontal and side (right, left) template.