Hair region localization with optical imaging for guided laser hair removal

Abstract

Laser hair removal is a popular nonsurgical aesthetic operation, where the aim is to remove unwanted hair permanently by damaging the hair follicle and shaft thermally. However, laser affects the superficial skin layers in addition to hair follicles causing health risks. Side effects of laser-assisted hair removal can be minimized by directing the laser beam only to the detected hair regions. This study proposes a feature-based hair region localization method using machine learning techniques, a first in this area. Features with low computational complexity have been proposed in order to discriminate hair and skin regions. Hair and skin region classification performances of different machine learning techniques have been applied and compared. Quantitative and visual results obtained from the proposed technique showed success in the detection of hair and skin regions. We concluded that the proposed method can be used in real-time guided laser hair removal devices.