Feature Based Hair Region Localization for Laser Hair Removal with Optical Imaging

Laser hair removal is a popular nonsurgical hair removal procedure, where the aim is to remove hair permanently by damaging the hair follicle and shaft thermally. However, currently available laser hair removal systems affect the superficial skin layers in addition to hair follicles causing health risks. Side effects of laser-assisted hair removal can minimized by directing the laser beam only to the detected hair regions. This study aims to develop a feature-based hair region localization method by using image processing and pattern recognition techniques as an integral part of the proposed laser hair removal system. We propose to detect hair regions by using two-stage feature based classification method based on machine learning techniques. The proposed two-stage classification method is aimed to improve the performance of the classifier. Performance of the proposed classifier is tested by using sensitivity and specificity values of the method and by measuring the processing time of the classifier. The results obtained from the proposed technique showed performance increase in hair region classification process.