Human Face Detection in Color Images Using HSV Color Histogram and WLD

In this paper, a new algorithm is proposed for detecting human faces in color images and as well as for removing background from a single face color image. The proposed algorithm combines color histogram for skin color (in the HSV space), a threshold value of gray scale image to easily detect skin regions in a given image. Then, in order to reduce the number of non-face regions, we calculate the number of holes of these selected regions. If the value is less than a particular threshold, then the region is selected. Also, ratio of the height and width of the detected skin region is calculated to differentiate face and non-face regions. Finally, Weber Local Descriptor (WLD) is calculated for each selected regions and then, each regions are divided into equal size block and corresponding entropy values of each block are calculated and compared with training samples to get the Euclidian distance between them. If the distance value is in between a tested threshold values, then the region block is face, otherwise it is non-face. The proposed algorithm has been tested on various real images and its performance is quite satisfactory.