As computers and the Internet become more and more available to families, access of objectionable graphics by children is increasingly a problem that many parents are concerned about. This paper describes WIPE™ (Wavelet Image Pornography Elimination), a system capable of classifying an image as objectionable or benign. The algorithm uses a combination of an icon filter, a graph-photo detector, a color histogram filter, a texture filter and a wavelet-based shape matching algorithm to provide robust screening of on-line objectionable images. Semantically-meaningful feature vector matching is carried out so that comparisons between a given on-line image and images in a pre-marked training data set can be performed efficiently and effectively. The system is practical for real-world applications, processing queries at a speed of less than 2 s each, including the time taken to compute the feature vector for the query, on a Pentium Pro PC. Besides its exceptional speed, it has demonstrated 96% sensitivity over a test set of 1076 digital photographs found on objectionable news groups. It wrongly classified 9% of a set of 10,809 benign photographs obtained from various sources. The specificity in real-world applications is expected to be much higher because benign on-line graphs can be filtered out with our graph-photo detector with 100% sensitivity and nearly 100% specificity, and surrounding text can be used to assist the classification process.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications