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A New Clustering Algorithm for Color Image Segmentation

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Pattern Recognition and Image Analysis (IbPRIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5524))

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Abstract

In this paper, we present a new data classification algorithm in an unsupervised context, which is based on both Kohonen maps and mathematical morphology. The first part of the proposed algorithm consists to a projection of the distribution of multidimensional data observations onto a Kohonen map which is represented by the underlying probability density function (pdf). Under the assumption that each modal region of this density function has a correspondance with a one and only one cluster in the distribution, the second part of the algorithm consists in partitioning the Kohonen map into connected modal regions by making concepts of morphological watershed transformation suitable for their detection. The classification process is then based on the so detected modal regions. As an application of the proposed algorithm, the sample of observations is constituted by image pixels with 3 color components in the RGB color space. The purpose is to present a new approach for unsupervised color image classification without using any thresholding procedure.

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References

  1. Devijver, P.A.: A statistical Approach. In: Pattern Recognition. Prentice-Hall, Englewood Cliffs (1982)

    Google Scholar 

  2. Bow, S.T.: Pattern Recognition, p. 323. Dekker, New York (1984)

    Google Scholar 

  3. Delsert, S.: Classification interactive non supervisée de données multidimensionnelles par réseaux de neurones à apprentissage compétitif, Thése de Doctorat, Université de Lille (1996)

    Google Scholar 

  4. Betrouni, M., Delsert, S., Hamad, D.: Interactive Pattern Classification by means of Artificial Neural Networks. In: IEEE, Int. Conf. on SMC, vol. IV, pp. 3275–3279 (October 1995)

    Google Scholar 

  5. Kohonen, S.: Self-organizing Maps, 2nd extended edn. Springer, Heidelberg (1997)

    Book  MATH  Google Scholar 

  6. Sadeghi, A.: A Self-organization properly of Kohonen’s map with general type of stimuli distribution. Neural Networks, 1637–1643 (1998)

    Google Scholar 

  7. Pal, N.R., Bezdek, J., Tsao, E.C.-K., et al.: Generalized Clustering Networks and Kohonen’s Self-Organizing Scheme. IEEE Trans. on Neural Networks 4(4), 549–557 (1993)

    Article  Google Scholar 

  8. Sbihi, A., Postaire, J.G.: Mode Extraction by Multivalue Morphology for Cluster Analysis. In: Gaul, W., Pfeifer, D. (eds.) From DATA to Knowledge: Theoretical and Practical aspects of classification, pp. 212–221. Springer, Berlin (1995)

    Google Scholar 

  9. Parzen, E.: On Estimation of a Probability Density Function and Mode. Ann. Math. Stat. 33, 1065–1076 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  10. Postaire, J.G., Vasseur, C.P.A.: An Approximate Solution to Normal Mixture Identification with Application to Unsupervised Pattern Classification. IEEE Trans. Patt. Anal. & Machine intel. PAMI-3(2), 163–179 (1981)

    Article  Google Scholar 

  11. Beucher, S., Lantuejoul, C.: Use of Watersheds in Contour Detection. In: Int. Workshop on Image Processing, CCETT / IRISA, Rennes (September 1979)

    Google Scholar 

  12. Postaire, J.-G., Zhang, R.D., Botte-Lecocq, C.: Cluster analysis by binary morphology. IEEE. Trans. Pattern Anal. Machine. Intell. PAMI-15(2), 170–180 (1993)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratoire de Recherche en Informatique LARI, Université Mohamed I, FSO, BP. 717, 60000, Oujda, Maroc, Morocco

    Mohammed Talibi Alaoui

  2. Laboratoire Images et Reconnaissance des Formes, LIRF, Université Ibn Tofail, FSK, B.P. 133, 14000, Kénitra, Maroc

    Abderrahmane Sbihi

Authors
  1. Mohammed Talibi Alaoui
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  2. Abderrahmane Sbihi
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Editor information

Editors and Affiliations

  1. Institute of Systems and Robotics, Dept. of Electrical and Computer Eng.-Polo II, University of Coimbra, 3030-290, Coimbra, Portugal

    Helder Araujo

  2. Institute of Biomedical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Ana Maria Mendonça

  3. Dept. de Electrónica e Telecomunicações / IEETA, Universidade de Aveiro, Signal Processing Lab, DETI/IEETA, University of Aveiro, 3810–193, Aveiro, Portugal

    Armando J. Pinho

  4. Departamento de Electricidad y Electrónica, Fac. Ciencia y Tecnología - UPV/EHU, Universidad del País Vasco, Apartado 644, 48080, Bilbao, Spain

    María Inés Torres

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© 2009 Springer-Verlag Berlin Heidelberg

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Talibi Alaoui, M., Sbihi, A. (2009). A New Clustering Algorithm for Color Image Segmentation. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_29

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  • DOI: https://doi.org/10.1007/978-3-642-02172-5_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02171-8

  • Online ISBN: 978-3-642-02172-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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