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SVM-Based Pornographic Images Detection

  • Haiming YinEmail author
  • Xiangqiong Huang
  • Yuanwang Wei
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 115)

Abstract

In this paper, we present a new automatic system for pornographic image detecting. An improved section skin model in RGB color space is employed to identify the rough skin regions. An original texture filter is used to modify these regions. Then the useful information of skin regions is extracted. Close-up face images are excluded by the face detection. At last all the information of skin and face is all fed to the SVM Classifier to tell whether the image is pornographic or not. Our experiments on real-world web image data indicate that our system can improve the accuracy of pornographic content detection significantly.

Keywords

pornographic image detection skin identifying texture filtering fractal dimension 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Computer Application Research LabJiaxing UniversityJiaxingChina

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