System for Screening Objectionable Images
Using Daubechies' Wavelets and Color Histograms
James Ze Wang, Gio Wiederhold, Oscar Firschein
Stanford University, Stanford, CA 94305
Abstract:
This paper describes WIPE (Wavelet Image Pornography Elimination), an
algorithm capable of classifying an image as objectionable or benign.
The algorithm uses a combination of Daubechies' wavelets, normalized
central moments, 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 efficiently and effectively. The system is practical for
real-world 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.
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Citation:
James Z. Wang, Gio Wiederhold and Oscar Firschein, ``System for
Screening Objectionable Images Using Daubechies' Wavelets and Color
Histograms,'' Lecture Notes in Computer Science, Special issue on
interactive distributed multimedia systems and telecommunication
services, Darmstadt, Germany, Ralf Steinmetz and Lars C. Wolf (eds.),
vol. 1309, pp. 20-30, Springer-Verlag, September 1997.
Copyright 1997 Springer-Verlag.
Published in the Proceedings of IDMS'97, September 10-12, 1997 in
Germany. Personal use of this material is permitted. However,
permission to reprint/republish this material for advertising or
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Last Modified:
01-Mar-97 22:10:45 PST
© 1997, James Z. Wang