System for Screening Objectionable Images Using Daubechies' Wavelets and Color Histograms

Abstract

This paper describes WIPE TM (Wavelet Image Pornography Eliminationan algorithm capable of classifying an image as objectionable or benign. The algorithm uses a combination of Daubechies' wavelets, normalized central ts, and color histograms to provide semantically-meaningful feature vector matching so that comparisons between the query image and images in a pre-marked training set can be performed effciently and effectively. The system is practical for realworld applications, processing queries at the speed of less than 10 seconds each, including the time to compute the feature vector for the query. Besides its exceptional speed, it has demonstrated 97.5 recall over a test set of 437 images found from objectionable news groups. It wrongly classified 18.4 of a set of 10,809 benign images obtained from various sources. For different application needs, the algorithm can be adjusted to show 95.2 recall while wrongly classifying only 10.7 of the benign images.