Face Detection in Coal Mine Surveillance Image Based on Skin Color and Face Template
煤矿监控图像中脸肤色和模板检测

The miner surveillance images arc of low contrast and unevenness gray level, which make the progress of processing and recognition very hard. Miner surveillance images from many angles arc sampled in laneway conditions. The miners' face areas of all angles can be segmented in HSV color space with up and bottom threshold value according to statistical characteristic of face color. The pixels which arc mis segmented can be wipped off with the open and close oporation in morphological with the circular structure clement of 2 pixels radius. An average face template based on the distribution feature of face gray level was constructed. A similarity functions was used as the discriminant functions to determine the locations of faces. I}hc results show that the locations of the miners' faces can be pinpointed fleetly with the method of face color segmentation and template matching.