Abstract
This paper presents a morphological classifier with application to color image segmentation. The basic idea of a morphological classifier is to consider a color histogram as a 3-D gray-level image, so that morphological operators can be applied to it. The final objective is to extract clusters in color space, that is, identify regions in the 3-D image. In this paper, we particularly focus on a powerful class of morphology-based filters called levellings to transform the 3- D histogram-image to identify clusters. We also show that our method gives better results than other state-of-the-art methods.
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REFERENCES
Barata, T. and Pina, P.(2002). Improving classification rates by modelling the clusters of training sets in features space using mathematical morphology operators. In Proceedings of the 16th Intl. Conf. on pattern Recognition, volume 4, pages 90–93, Quebec City, Canada. IEEE Computer Society.
Comaniciu, D. and Meer, P.(1997). Robust analysis of feature spaces: Color image segmentation. In Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pages 750–755, San Juan, Puerto Rico.
Darbon, J., Geraud, T., and Duret-Lutz, A. (2002). Generic implementation of morphological image operators. In Mathematical Morphology, Proceedings of the 6th Intl. Symposium (ISMM), pages 175–184. Sciro Publishing.
Deriche, R. (1993). Recursively implementing the gaussian and its derivatives. Technical Report 1893, INRIA.
Geraud, T. (2003). Fast road network extraction in satellite images using mathematical morphology and markov random fields. In Proceedings of the EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP), Trieste, Italy.
Geraud, T., Strub, P.Y., and Darbon, J. (2001). Color image segmentation based on automatic morphological clustering. In Proceedings of the IEEE Intl. Conf. on Image Processing, volume 3, pages 70–73.
Meijster, A. and Wilkinson, M.H.F. (2002). A comparison of algorithms for connected set openings and closings. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(4):484–494.
Park, S.H., Yun, I.D., and Lee, S.U. (1998). Color image segmentation based on 3-D clustering: Morphological approach. Pattern Recognition, 31(8):1061–1076.
Postaire, J.-G., Zhang, R.D., and Lecocq-Botte, C. (1993). Cluster analysis by binary morphology. IEEE Trans. on PAMI, 15(2):170–180.
Serra, J. and Salembier, P. (1993). Connected operators and pyramids. In Proceedings of SPIE Image Algebra and Mathematical Morphology IV, volume 2030, pages 65–76, San Diego, CA, USA.
Soille, P. (1999). Morphological Image Analysis - Principles and Applications. Springer-Verlag.
Vachier, C. (2001). Morphological scale-space analysis and feature extraction. In Proceedings of IEEE Intl. Conf. on Image Processing, volume 3, pages 676–679, Thessaloniki, Greece.
Vincent, L. and Soille, P. (1991). Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans. on PAMI, 13(6):583–598.
Zhang, R.D. and Postaire, J.-G. (1994). Convexity dependent morphological transformations for mode detection in cluster analysis. Pattern Recognition, 27(1): 135–148.
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Geraud, T., Palma, G., Van Vliet, N. (2006). FAST COLOR IMAGE SEGMENTATION BASED ON LEVELLINGS IN FEATURE SPACE. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_116
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DOI: https://doi.org/10.1007/1-4020-4179-9_116
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