Neural network based adult image classification

  • Authors:
  • Wonil Kim;Han-Ku Lee;Seong Joon Yoo;Sung Wook Baik

  • Affiliations:
  • College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea;School of Internet and Multimedia Engineering, Konkuk University, Seoul, Republic of Korea;College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea;College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea

  • Venue:
  • ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
  • Year:
  • 2005

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Abstract

Digital multimedia data is dramatically being increased everyday since the Internet became popular. This increment in multimedia data increases adult image contents to the Internet as well. Consequently, a large number of children are exposed to these X-rated contents. In this paper, we propose an efficient classification system that can categorize input images into adult or non-adult images. The simulation shows that this system achieved 95% of the true rate whereas it reduces the false positive rate below 3%.