Face Detection in Color Image using Rectangle Feature

Abstract

We propose a rectangle feature set utilizing multiple color space information for human face detection. Images of RGB color space can be converted into normalized RGB and HSV color spaces and thus the interference of lighting conditions can be reduced. Base on this mechanism, we define 8 rectangle features inside 4 selected color spaces and use a boosting algorithm to select the important features. Experimental results show that the detectors constructed with our approach are able to process nearly one million sub-windows within 2.4 seconds. The selected color features are mostly in Hue domain. These results show the classifying ability of multiple color spaces analysis as well as the possibility to develop a faster system based on the color features.