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System for screening objectionable images using Daubechies' wavelets and color histograms

  • James Ze WangEmail author
  • Gio Wiederhold
  • Oscar Firschein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1309)

Abstract

This paper describes WIPETM (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 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.

Keywords

Feature Vector Objectionable Image Query Image Color Histogram Central Moment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • James Ze Wang
    • 1
    Email author
  • Gio Wiederhold
    • 1
  • Oscar Firschein
    • 1
  1. 1.Department of Computer ScienceStanford UniversityStanford

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