DOI QR코드

DOI QR Code

A Natural Scene Statistics Based Publication Classification Algorithm Using Support Vector Machine

서포트 벡터 머신을 이용한 자연 연상 통계 기반 저작물 식별 알고리즘

  • Song, Hyewon (Yonsei University, Department of Electrical and Electronic Engineering) ;
  • Kim, Doyoung (Yonsei University, Department of Electrical and Electronic Engineering) ;
  • Lee, Sanghoon (Yonsei University, Department of Electrical and Electronic Engineering)
  • Received : 2016.12.29
  • Accepted : 2017.04.26
  • Published : 2017.05.31

Abstract

Currently, the market of digital contents such as e-books, cartoons and webtoons is growing up, but the copyrights infringement are serious issue due to their distribution through illegal ways. However, the technologies for copyright protection are not developed enough. Therefore, in this paper, we propose the NSS-based publication classification method for copyright protection. Using histogram calculated by NSS, we propose classification method for digital contents using SVM. The proposed algorithm will be useful for copyright protection because it lets us distinguish illegal distributed digital contents more easily.

References

  1. Y. Ryu, Global e-book market status and prospects(2015), Retrieved Aug. 12, 2015, from http://www.slideshare.net/pageraum2/201508-51546993
  2. S. J. Jang, "Design of the copyright protection for ePub e-Book system using certification information," JKIICE, vol. 19, no. 9, pp. 2197-2204, Sept. 2015.
  3. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Computer Vision, vol. 60, no. 2, pp. 91-110, Nov. 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  4. H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool, "Speeded-up robust features (SURF)," Computer vision and image understanding, vol. 110, no. 3, pp. 346-359, Jun. 2008. https://doi.org/10.1016/j.cviu.2007.09.014
  5. J. S. Song, S. J. Hur, Y. W. Park, and J. H. Choi, "User positioning method based on image similarity comparison using single camera," J. KICS, vol. 40, no. 8, pp. 1655-1666, Aug. 2015. https://doi.org/10.7840/kics.2015.40.8.1655
  6. H. J. Jung and J. S. Yoo, "Feature matching algorithm robust to viewpoint change," J. KICS, vol. 40, no. 12, pp. 2363-2371, Dec. 2015. https://doi.org/10.7840/kics.2015.40.12.2363
  7. W. J. Han and K. A. Sohn, "Image classification approach for improving CBIR system performance," J. KICS, vol. 41, no. 7, pp. 816-822, Jun. 2016. https://doi.org/10.7840/kics.2016.41.7.816
  8. D. Ciregan, M. Ueli, and S. Jurgen, "Multi-column deep neural networks for image classification," CVPR, pp. 3642-3649, Rhode island, USA, Jun. 2012.
  9. S. G. Kim and B. G. Kang, "An implementation of pattern recognition algorithm for fast paper currency counting," J. KICS, vol. 39B, no. 7, pp. 459-466, Jun. 2014. https://doi.org/10.7840/kics.2014.39B.7.459
  10. M. Anish, S. Rajiv, and A. C. Bovik, "Making a "completely blind" image quality analyzer," IEEE Sign. Process. Let., vol. 20, no. 3, pp. 209-212, Mar. 2013. https://doi.org/10.1109/LSP.2012.2227726
  11. J. A. K. Suykens and J. Vandewalle, "Least squares support vector machine classifiers," Neural Process. Lett, vol. 9, no. 3, pp. 293-300, Jun. 1999. https://doi.org/10.1023/A:1018628609742
  12. P. John, "Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods," Advances in Large Margin Classifiers, vol. 10, no. 3, pp. 61-74, Mar. 1999.