Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Detection of Harmful Images Based on Color and Geometrical Features

색상과 기하학적인 특징 기반의 유해 영상 탐지

  • 장석우 (안양대학교 디지털미디어학과) ;
  • 박영재 (숭실대학교 컴퓨터학부) ;
  • 허문행 (안양대학교 디지털미디어학과)
  • Received : 2013.08.12
  • Accepted : 2013.11.07
  • Published : 2013.11.30
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Abstract

Along with the development of high-speed, wired and wireless Internet technology, various harmful images in a form of photos and video clips have become prevalent these days. In this paper, we suggest a method of automatically detecting adult images by extracting woman's nipple areas which represent obscenity of the image. The suggested algorithm first segments skin color areas in the $YC_bC_r$ color space from input images and extracts nipple's candidate areas from the segmented skin areas through the suggested nipple map. We then select real nipple areas by using geometrical information and determines input images as harmful images if they contain nipples. Experimental results show that the suggested nipple map-based method effectively detects adult images.

최근 들어, 초고속의 유무선 인터넷과 스마트 기기가 널리 보급됨에 따라 사진이나 동영상 형태의 유해 영상들이 급속히 보급되고 있다. 본 논문에서는 입력되는 영상에서 음란성을 대표하는 여성의 유두 영역을 자동으로 추출하여 유해 영상을 보다 효과적으로 탐지하는 새로운 방법을 제안한다. 제안된 알고리즘은 먼저 입력된 영상의 RGB 색상공간을 $YC_bC_r$ 공간으로 변환하여 사람의 피부색상 영역을 검출한다. 그리고 본 논문에서 새롭게 정의한 유두 맵을 적용하여 검출된 피부 영역으로부터 유두의 후보 영역들을 추출한다. 그런 다음, 기하학적인 특징을 사용하여 유두의 후보영역 중에서 실제 유두 영역만을 강건하게 필터링하고, 여성의 유두 영역을 포함하고 있는 영상을 유해한 영상이라고 판단한다. 성능을 비교 평가하는 실험결과에서는 제안된 색상과 기하학적인 특징 기반의 알고리즘이 유해 영상을 기존의 방법에 비해 보다 정확하게(4.1% 향상) 탐지한다는 것을 실험을 통해 보여준다.

Keywords

References

  1. S.-W. Jang, Y.-J. Park, G.-Y. Kim, H.-I. Choi, M.-C. Hong, "An Adult Image Identification System Based on Robust Skin Segmentation," Journal of Imaging Science and Technology, Vol. 55. No. 2, pp. 020508-1-10, March 2011. DOI: http://dx.doi.org/10.2352/J.ImagingSci.Technol.2011.55.2.020508
  2. J.-S. Lee, Y.-M. Kuo, P.-C. Chung, and E-L. Chen, "Naked Image Detection Based on Adaptive and Extensible Skin Color Model," Pattern Recognition, Vol. 40, No. 8, pp. 2261-2270, August 2007. DOI: http://dx.doi.org/10.1016/j.patcog.2006.11.016
  3. J.-L. Shih, C.-H. Lee, and C.-S. Yang, "An Adult Images Identification System Employing Image Retrieval Technique," Pattern Recognition Letters, Vol. 28, No. 16, pp. 2367-2374, December 2007. DOI: http://dx.doi.org/10.1016/j.patrec.2007.08.002
  4. Q.-F. Zheng, W. Zeng, G. Wen, and W.-Q. Wang, "Shape-based Adult Images Detection," In Proc. of the IEEE Symposium on Multi-Agent Security and Survivability, pp. 150-153, December 2004. DOI: http://dx.doi.org/10.1109/ICIG.2004.128
  5. S.-W. Jang, S.-I. Joo, G.-Y. Kim, "Active Shape Model-based Objectionable Images Detection," Journal of Korean Society for Internet Information, Vol. 10, No. 5, pp. 71-82, October 2009.
  6. A. Cheddad, J. Condell, K. Curran, and P. M. Kevitt, "A Skin Tone Detection Algorithm for an Adaptive Approach to Steganography," Signal Processing, Vol. 89, No. 12, pp. 2465-2478, December 2009. DOI: http://dx.doi.org/10.1016/j.sigpro.2009.04.022
  7. R.-L. Hsu, M. Abdel-Mottaleb, and A. K. Jain, "Face Detection in Color Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 5, pp. 696-706, May 2002. DOI: http://dx.doi.org/10.1109/34.1000242
  8. N. Otus, "A Threshold Selection Method from Gray-Level Histogram," IEEE Transactions on Systems, Man and Cybernetics, Vol. 9, No. 1, pp. 62-66, January 1979. DOI: http://dx.doi.org/10.1109/TSMC.1979.4310076
  9. M. Sezgin and B. Sankur, "Survey over Image Thresholding Techniques and Quantitative Performance Evaluation," Journal of Electronic Imaging, Vol. 13, No. 1, pp. 146-165, January 2004. DOI: http://dx.doi.org/10.1117/1.1631315
  10. K. Kim, "Boundary-Checking-Free Implementation of Connected-Component Labeling," Journal of Korean Institute of Information Technology, Vol. 11, No. 5, pp. 53-61, 2013.
  11. L. He, Y. Chao, K. Suzuki, and K. Wu, "Fast Connected-Component Labeling," Pattern Recognition, Vol. 42, No. 9, pp. 1977-1987, 2009. DOI: http://dx.doi.org/10.1016/j.patcog.2008.10.013
  12. Y.-S. Im, E.-Y. Kang, "Watermarking and QR Code in Digital Image Coding", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 12, No 6, pp. 99-104, 2012.
  13. G.-B. Kim, S.-H. Song, K.-J. Yoon, "Design and Fabrication of Multi-rotor system for Vision based Autonomous Landing", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 12, No 6, pp. 141-146, 2012.
  14. W. Kim, "Design of Visual Surveillance System based on Wireless High Definition Image Transmission Technology", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 12, No 5, pp. 25-30, 2012.
  15. S.-J. Kim, "Medical Image Enhancement Using an Adaptive Weight and Threshold Values", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 12, No 5, pp. 205-211, 2012.
  16. S.-B. Ryu, M.-S. Kang, "Implementation of Image Security System for CCTV Using Analysis Technique of Color Informations", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 12, No 5, pp. 219-227, 2012. https://doi.org/10.7236/JIWIT.2012.12.5.219

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