Detección de rostros humanos en posición frontal en imágenes a color utilizando propiedades estadísticas de la piel humana junto con el método de concordancia con el rostro plantilla

Abstract

A method for detecting human faces in color images was developed and implemented, consisting of three main steps: human color statistics, adaptive thresholding process and Template Matching. A skin model determines the most likely skin regions in an image. This skin model is made from 20 skin samples from persons of different ethnicity, which color distribution in the chromatic color space generates a chroma chart showing likelihood of skin colors. The image is transformed into a gray scale image using this chart; the gray value at a pixel shows the likelihood of the pixel representing skin. Then this gray scale image is segmented to skin and non-skin regions using an adaptive thresholding process to achieve the optimal value. A fixed threshold value is not possible to be found, since people with different skins have different likelihood. Finally, the template matching determines if a given skin region represents a frontal human face.