Data-Mining Based Skin-Color Modeling Using the ECL Skin-Color Images Database

  • Mohamed Hammami
  • Dzmitry Tsishkou
  • Liming Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)


Many human image processing techniques use skin detection as a first stage in subsequent feature extraction. In this paper we describe methods of skin detection using a data-mining technique. We also show the importance of the choice of the base simple to the performance of our skin analysis techniques. We present the details and the process of construction of our database which we have called “the ECL Skin-color Images Database from video ”. We will show that the use of a database derived from live video gives better results than one derived from internet images for face detection in video application.


Face Detection Binary Mask Color Pixel Skin Detection Internet Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Albiol, A., Torres, L., Bouman, C.A., Delp, E.J.: A simple and efficient face detection algorithm for video database applications. In: Proceedings of the IEEE International Conference on Image Processing, Vacouver, Canada, September 2000, vol. 2, pp. 239–242 (2000)Google Scholar
  2. 2.
    Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification of Regression Trees. Wadsworth (1984)Google Scholar
  3. 3.
    Fayyad, U.M., Djorgovski, S.G., Weir, N.: Automating the analysis and cataloging of sky surveys. In: Fayyad, U., PiatetskyShapiro, G., Smyth, P., Uthurusamy, R. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 471–493. AAAI/MIT Press (1996)Google Scholar
  4. 4.
    Hammami, M., Chahir, Y., Chen, L., Zighed, D.: Détection des régions de couleur de peau dans l’image, revue RIA-ECA, vol. 17, Ed.Hermès, pp. 219–231 (Janvier 2003) ISBN 2-7462-0631-5Google Scholar
  5. 5.
    Hammami, M., Chahir, Y., Chen, L.: Combining Text and Image Analysis in The Web Filtering System: WebGuard. In: IADIS International Conference: WWW/Internet 2003, Algarve, Portugal, November 5-8, pp. 611–618 (2003) ISBN 972-98947-1-XGoogle Scholar
  6. 6.
    Jones, M.J., Regh, J.M.: Statistical Color Models with application to Skin Detection, Cambridge Research Laboratory, CRL 98/11 (1998)Google Scholar
  7. 7.
    Quinlan, J.R.: Induction of decision trees. Machine Learning 1, 81–106 (1986)Google Scholar
  8. 8.
    Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)Google Scholar
  9. 9.
    Tock, D., Craw, I.: Tracking and measuring drivers’ eyes. Image and Vision Computing 14, 541–548 (1996)CrossRefGoogle Scholar
  10. 10.
    Wang, H., Chang, S.-F.: A highly efficient system for automatic face region detection in mpeg video. IEEE Transactions on circuits and system for video technology 7(4), 615–628 (1997)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Wang, J.G., Sung, E.: Frontal-view face detection and facial feature extraction using color adn morphological operators. Pattern recognition letters 20(10), 1053–1068 (1999)CrossRefGoogle Scholar
  12. 12.
    Yang, M.-H., Ahuja, N.: Detecting human faces in color images. In: Proceedings of the International Conference on Image Processing, Chicago, IL, October 4-7, pp. 127–130 (1998)Google Scholar
  13. 13.
    Zighed, D.A., Rakotomala, R.: A method for non arborescent induction graphs. Technical report, Laboratory ERIC, University of Lyon 2 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Mohamed Hammami
    • 1
  • Dzmitry Tsishkou
    • 1
  • Liming Chen
    • 1
  1. 1.LIRISFRE 2672 CNRS, Ecole Centrale de LyonEcullyFrance

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