The Naked Image Detection Based on Automatic White Balance Method

Abstract

This paper presents a new naked image detection system. We propose the skin tone sampling algorithm based on automatic white balance method. The goal of white balance is to correct the image such that it looks as if it is taken in the canonical light. First, the uniform skin chromatic distribution is established manually from the skin images taken under the canonical light. After the target image is corrected by the white balance method based on the canonical light, the skin objects in the target image can be segmented by the uniform skin chromatic distribution. The texture feature, coarseness, is also utilized to acquire the more accurate skin regions. Then, the back propagation neural network is used to integrate several low-level and reliable geometrical constraints into a classifier to inspect the skin regions further. Finally, the mug shot exclusion procedure is applied to promote the system performance. The experimental results show our method is satisfactory for naked image detection.