Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A Lip Detection Algorithm Using Color Clustering

색상 군집화를 이용한 입술탐지 알고리즘

  • Jeong, Jongmyeon (Dept. of Computer Engineering, Mokpo National Maritime University)
  • 정종면 (목포해양대학교 해양컴퓨터공학과)
  • Received : 2014.01.21
  • Accepted : 2014.02.18
  • Published : 2014.03.31
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Abstract

In this paper, we propose a robust lip detection algorithm using color clustering. At first, we adopt AdaBoost algorithm to extract facial region and convert facial region into Lab color space. Because a and b components in Lab color space are known as that they could well express lip color and its complementary color, we use a and b component as the features for color clustering. The nearest neighbour clustering algorithm is applied to separate the skin region from the facial region and K-Means color clustering is applied to extract lip-candidate region. Then geometric characteristics are used to extract final lip region. The proposed algorithm can detect lip region robustly which has been shown by experimental results.

본 논문에서는 색상 군집화를 이용한 입술탐지 알고리즘을 제안한다. RGB 색상 모델로 주어진 입력영상에서 AdaBoost 알고리즘을 이용하여 얼굴영역을 추출한 후, 얼굴영역을 Lab 컬러 모델로 변환한다. Lab 컬러 모델에서 a 성분은 입술과 유사한 색상을 잘 표현할 수 있는 반면 b 성분은 입술의 보색을 표현할 수 있기 때문에 Lab 컬러로 표현된 얼굴영역에서 a와 b 성분을 기준으로 최단 이웃(nearest neighbour) 군집화 알고리즘을 이용하여 피부 영역을 분리한 후, K-means 색상 군집화를 통해 입술 후보 영역을 추출하고, 마지막으로 기하학적 특징을 이용하여 최종적인 입술영역을 탐지하였다. 실험 결과는 제안된 방법이 강건하게 입술을 탐지함을 보인다.

Keywords

References

  1. A. Hulbert, T. Poggio, "Synthesizing a color algorithm from examples," Science, New Series, vol. 239, pp. 482-485, 1998.
  2. U. Canzlerm, T. Dziurzyk, "Extraction of non manual features for video based sign language recognition", Proc. of IAPR Workshop, pp. 318-321, 2002.
  3. X. Zhang, R. M. Mersereau, "Lip feature extraction toward an automatic speech reading system", Proc. of IEEE Int. Conf. Image Processing, vol. 3, pp. 226-229, 2000.
  4. M. G. Song, T. T. Pham, J. Y. Kim and S. T. Hwang, "A Study on Lip Detection based on Eye Localization for Visual Speech Recognition in Mobile Environment", Journal of KSCI, Vol. 19, No. 4, pp. 478-484, 2009. https://doi.org/10.5391/JKIIS.2009.19.4.478
  5. K. H. Lee, "Face Tracking Using Face Feature and Color Information", Journal of KSCI, Vol. 18. No. 11, pp. 167-174, 2013. https://doi.org/10.9708/jksci.2013.18.11.167
  6. P. S. Aleksic, J. J. Williams, Z. Wu, A. K. Katsaggelos, "Audiovisual speech recognition using MPEG-4 compliant visual features", EURASIP J. Appl. Signal Processing. pp. 1213-1227, 2002.
  7. R. Kaucic, B. Dalton, A. Blake, "Real-time lip tracking for audio-visual speech recognition applications", Lecture Notes in Computer Science, Vol. 1065, pp. 376-387, 1996.
  8. S. Werda, W. Mahdi, A. Ben-Hamadou, "Colour and geometric based model for lip localization: application for lip-reading system", 14th International Conference on Image Analysis and Processing, pp.9-14, 2007.
  9. C. Bouvier, P.-Y. Coulon, X. Maldague, "Unsupervised lips segmentation based on ROI optimization and parametric model", IEEE International Conference on Image Processing, Vol. 4, pp. 301-304, 2007.
  10. S. W. Chin and K. P. Sengs, "Improved watershed lips detection and modified $H^{\infty}$ tracking system based on lyapunov stability theory", Int'l Conference on IHMSC, Vol. 2, pp. 355-358, 2009.
  11. L. Wang, X. Wang and J. Xus, "Lip detection and tracking using variance based Haar-like features and Kalman filter", Int'l Conference on FCST, pp. 608-612, 2010.
  12. Y. H. Huang, B. C. Pan, S. L. Zheng, J. Pan and Y. Tangs, "Lip-reading detection and localization based on two stage ellipse fitting", Int'l Conference on ICWAPR, Vol. 1, pp. 168-171, 2008.
  13. Y. Pingxian and G. Rongs, "Research on lip detection based on OpenCV", Int'l Conference on TMEE, pp. 1465-1468, 2011.
  14. E. Skodras and N. Fakotakis, "An unconstrained method for lip detection in color images", Int'l Conference on ICASSP, pp. 1013-1016, 2011.
  15. R. Duda, P. Hart, D. Stork, "Pattern Classification" 2nd Edition, pp. 474-482, A Wiley-Interscience Publication, 2000.
  16. P. Viola and M. Jones, "Rapid object using a boosted cascade of simple features", IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. I.511 - I.518, 2001.
  17. A. K. Jain, "Fundamentals of digital image processing", Prentice-Hall, pp. 66-71, 1989.
  18. J. T. Tou, R. C. Gonzalez, "Pattern recognition principles", Addison-Wesley Publishing Company Inc., pp. 75-83, pp. 94-97, 1974.