The Design of a Hybrid Feature Detector for Adult Images

Adult image detection is an important issue lately due to the parental control needs. Skin color detector is a typical solution for adult image detection. However, the performance needs to be improved due to the lack of color photo diversity. Even Bag-of-Visual-Words (BoVWs) approaches is another scheme to solve this problem, it is not easy to get efficient solution. In this paper, a hybrid feature detector for adult images is proposed. The method normalizes the local feature and global feature to become a hybrid feature which combines the benefits between BoVWs and skin-color-detector. Experimental results demonstrate that its computation time is shorter than the one of BoVWs technique and almost equivalent to the one of skin-color-detector. The most important fact of all is that the hybrid feature detector has achieved better accuracy ratio than the results by using BoVWs or skin-color-detector techniques.