Eye Detection Based on Skin Color Analysis with Different Poses under Varying Illumination Environment

Abstract

In this paper, we propose a method of eye detection based on skin color analysis under varying illumination. The proposed method consists of several phases, including color conversion, skin color segmentation and face mask calculation, facial feature extraction and eye candidate determination, and detection of human eyes. To eliminate the effect of lighting change on the performance of eye detection, color conversion is first performed. Face mask calculation based on skin color segmentation is then carried out to reduce the possible searching region of human eyes. Eye candidates detected using facial features are used to define the possible human eyes. Human eyes are thus detected by the geometric features of gravity and spatial centers for these eye candidates. Results show that the proposed method works well for faces with different poses and multiple faces under varying illumination. The eye detection time of 21.8 ms is achieved for an image of size 213×320 pixels, indicating computational efficiency of the proposed system.