Detecting Faces According to their Pose

Human face detection is one of the vital techniques in computer vision. It plays so important role in a wide variety of applications such as surveillance systems, video tracking applications and image database management. In this paper a new method to detect faces with different pose in colour images, is proposed. Skin colour, lip position, face shape information and statistical texture properties are the key parameters for developing fussy rule based classifiers to extract face candidate from an image. The algorithm consist of two main parts: detecting frontal face system and detecting profile face system. In first step, skin regions are identified in HSI colour space, using fuzzy system, applying distance of each pixel colour to skin colour cluster as input and producing a skin-likelihood image in output. The regions owning the most likelihood of belonging to skin are labelled and enter the frontal face detecting part . To extract frontal face regions ,fuzzy rule based system is used, applying face and lip position, lip area data and face shape. The detected faces are removed and remain areas are tested by the profile face finding algorithm. This algorithm utilizes statistical texture properties of ear to verify profile face detection. By this system, 98%, 90% and 83.33% detection rates are achieved, respectively for frontal, near frontal and profile faces.