Illumination - Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods
Suhaila N. Mohammed *
Department of Computer Science, College of Science, Baghdad University, Baghdad, Iraq.
Loay E. George
Department of Computer Science, College of Science, Baghdad University, Baghdad, Iraq.
*Author to whom correspondence should be addressed.
Abstract
The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material a subset consists of 1150 images belong to 91 different subjects was taken from Cohn-Kanade AU coded dataset (CK); the subjects images hold different facial expressions. The test results show the effectiveness of the proposed automated localization scheme in different illuminations conditions; it gave accuracy of about 95.7%.
Keywords: Facial components, illumination invariant, adaptive gamma correction, adaptive contrast stretching, image segmentation