Blocking objectionable images: adult images and harmful symbols

This paper describes a practical objectionable image filtering system, aimed at children´s safer Web access. It includes two image filters: adult image filter and harmful symbol filter. In the adult image filter, we adopt a statistical model for skin detection and a neural network for adult image classification. The performance of the skin detection of our model outperforms that of the baseline model. Its elapsed time is about 0.18 second per image, which compares very well against previous systems. In the harmful symbol filter, we present an edge based Zernike moments method, which can capture the shape feature of a symbol object effectively. Its elapsed time is about 0.13 second per image. Experimental results on a large image database show that both of our filters can give promising performances