In this paper, a vision-based method is proposed to automatically recognize the hair follicles and plan the cutting path to separate them into units. By using color information and machine learning, hair area in the image can be recognized. And the interferences such as adipose shadows and scalpel parts will be eliminated by texture and area information. In order to recognize single piece of hair, a curve detection method is proposed which combine the linear Hough transform and the quadratic curve fitting method to detect hair pieces with follicles on them. After determining the location and distribution of hair follicles, based on the hair growth direction and the minimum external rectangle of hair area, cutting path will be planned to separate each follicular unit. Compared with the traditional artificial hair follicular unit separation, this method not only ensures the fitting accuracy, but also speeds up the processing speed.
['Bohan Yang', 'Hesheng Wang', 'Weidong Chen', 'Yusen Liang']
Vision-Based Automatic Hair Follicular Unit Separation