Deise Santana MaiaRoque Mendes Prado Trindade
In this paper we describe our implementation of algorithms for face detection and recognition in color images under Matlab. For face detection, we trained a feedforward neural network to perform skin segmentation, followed by the eyes detection, face alignment, lips detection and face delimitation. The eyes were detected by analyzing the chrominance and the angle between neighboring pixels and, then, the results were used to perform face alignment. The lips were detected based on the analysis of the Red color component intensity in the lower face region. Finally, the faces were delimited using the eyes and lips positions. The face recognition involved a classifier that used the standard deviation of the difference between color matrices of the faces to identify the input face. The algorithms were run on Faces 1999 dataset. The proposed method achieved 96.9%, 89% and 94% correct detection rate of face, eyes and lips, respectively. The correctness rate of the face recognition algorithm was 70.7%.
Jae Young ChoiYong Man RoKonstantinos N. Plataniotis
Rein-Lien HsuMohamed Abdel-MottalebAnil K. Jain
Rein-Lien HsuMohamed Abdel-MottalebAnil K. Jain
Jin Ok KimSung Jin SeoChin Hyun ChungJun HwangWoongjae Lee
Shahad laith abd al galibAsma Abdulelah AbdulrahmanFouad Shaker Tahir Al-azawi