Face Skin Color Area Segmentation in Laneway Surveillance Images
It is very difficult to segment the faces in coal mine laneway surveillance images.The miners'surveilled images are sampled at typical surveilling angles in laneway.The statistic feature of miners'face color is analyzed separately in tri-component of HSV color model.The pixels of skin color area and the background ones that seem to shin color ones are segmented based on the segmentation method with upper and lower threshold value.The influence of background pixels is decrease observably and the region of face is reduced,after the binary images of faces is smoothed and segmented.The results of experiments show that the method above is simple and celerity in computing and can segment the faces area in laneway surveillance images successfully.