Non-retrieval: Blocking Pornographic Images

  • Alison Bosson
  • Gavin C. Cawley
  • Yi Chan
  • Richard Harvey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2383)


We extend earlier work on detecting pornographic images. Our focus is on the classification stage and we give new results for a variety of classical and modern classifiers. We find the artificial neural network offers a statistically significant improvement. In all cases the error rate is too high unless deployed sensitively so we show how such a system may be built into a commercial environment.


Support Vector Machine Receiver Operating Characteristic Curve Colour Space Near Neighbour Multilayer Perceptron 
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 2002

Authors and Affiliations

  • Alison Bosson
    • 1
  • Gavin C. Cawley
    • 2
  • Yi Chan
    • 2
  • Richard Harvey
    • 2
  1. 1.Clearswift CorporationThealeUK
  2. 2.School of Information SystemsUniversity of East AngliaNorwichUK

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