Pornographic image screening by integrating recognition module and image black-list/ white-list subsystem

A number of pornographic image detection techniques have been studied in the literature but the online error-correction method is rarely discussed. As some of the pornographic images on the Internet are duplicated, the online error-correction capability can prevent repeated misclassification occurring on the same image. An image black-list/white-list subsystem is presented to correct the classification errors of the recognition module. This subsystem uses the wavelet transform to extract the colour and texture features from images. However, images can be lossily compressed and the image features will be shifted. To be able to identify lossily compressed images, a support vector machine serves as a classifier to determine whether two image feature vectors represent the same image. The experimental result demonstrates that the proposed subsystem can remedy the errors of the recognition module and increase the recognition accuracy.