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Proceedings Paper

Automatic system for detecting pornographic images
Author(s): Kevin I. C. Ho; Tung-Shou Chen; Jun-Der Ho
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Paper Abstract

Due to the dramatic growth of network and multimedia technology, people can more easily get variant information by using Internet. Unfortunately, it also makes the diffusion of illegal and harmful content much easier. So, it becomes an important topic for the Internet society to protect and safegurard Internet users from these content that may be encountered while surfing on the Net, especially children. Among these content, porno graphs cause more serious harm. Therefore, in this study, we propose an automatic system to detect still colour porno graphs. Starting from this result, we plan to develop an automatic system to search porno graphs or to filter porno graphs. Almost all the porno graphs possess one common characteristic that is the ratio of the size of skin region and-skin region is high. Based on this characteristic, our system first converts the colour space from RGB colour space to HSV colour space so as to segment all the possible skin-colour region from scene background. We also apply the texture analysis on the selected skin-colour region to separate the skin region from non-skin region. Then we try to group the adjacent pixels located in skin region. If the ratio is over a given threshold, we can tell if the given image is a possible porno graph. Based on our experiment, less than 10% of non-porno graphs are classified as pornography, and over 80% of the most harmful porno graphs ara classified correctly.

Paper Details

Date Published: 13 September 2002
PDF: 10 pages
Proc. SPIE 4922, Color Science and Imaging Technologies, (13 September 2002); doi: 10.1117/12.483143
Show Author Affiliations
Kevin I. C. Ho, Chung Shan Medical Univ. (Taiwan)
Tung-Shou Chen, National Taichung Institute of Technology (Taiwan)
Jun-Der Ho, National Taichung Institute of Technology (Taiwan)

Published in SPIE Proceedings Vol. 4922:
Color Science and Imaging Technologies
Dazun Zhao; Ming Ronnier Luo; Kiyoharu Aizawa, Editor(s)

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