Hierarchical Segmentation Using Dynamics of Multiscale Color Gradient Watersheds
In this paper, we describe and compare two multiscale color segmentation schemes basedon the Gaussian multiscale and the Perona and Malik anisotropic difusion. The proposed segmentation schemes consist of an extension to color images of an earlier multiscale hierarchical watershedsegm entation for scalar images. Our segmentation scheme constructs a hierarchy among the watershed regions using the principle of dynamics of contours in scale-space. Each contour is valuated by combining the dynamics of contours over the successive scales. We conduct experiments on the scale-space stacks created by the Gaussian scale-space and the Perona and Malik anisotropic difusion scheme. Our experimental results consist of the comparison of both schemes with respect to the following aspects: size andin formation reduction between successive levels of the hierarchical stack, dynamics of contours in scale space and computation time.
KeywordsColor Image Hierarchical Level Mathematical Morphology Segmentation Scheme Mosaic Image
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- 1.S. Beucher. Watershed, hierarchical segmentation and waterfall algorithm. In J. Serra and P. Soille, editors, Mathematical Morphology and its applications on Image and Signal processing (ISMM’94), pages 69–76. Kluwer Academic Press, 1994.Google Scholar
- 2.J. Bosworth, T. Koshimizu and S.T. Acton. Automated Segmentationof Surface Soil Moisture From Landsat TM Data, In Proc. of the IEEE Southwest Symposium on Image Analysis and Interpretation, Tucson, April 6-7, 1998.Google Scholar
- 4.J. Crespo and R. Schafer. The flat zone approach and color images. In J. Serra and P. Soille, editors, Mathematical Morphology and its applications on Image and Signal processing (ISMM’94), pages 85–92. Kluwer Academic Press, 1994.Google Scholar
- 5.C.H. Demarty and S. Beucher. Color segmentation algorithm using an HLStr ansformation. In H. Heijmans and J. Roerdink, editors, Mathematical Morphology and its applications on Image and Signal processing (ISMM’98), pages 231–238. Kluwer Academic Press, 1998.Google Scholar
- 6.P. De Smet, R. Pires, D. De Vleeschauwer, I. Bruyland. Activity driven non-linear difusion for color image watershed segmentation. Journal of Electronic Imaging (SPIE), Volume 08(03), 1999.Google Scholar
- 7.F. Meyer. Color image segmentation. In 4th IEEE Conference on Image Processing and applications, volume 354:53Google Scholar
- 10.I. Pratikakis, H. Sahli, and J. Cornelis. Hierarchical segmentation using dynamics of multiscale gradient watershed. 11th Scandinavian Conference on Image Analysis 99, pp. 577–584, 1999.Google Scholar
- 11.I. Vanhamel, I. Pratikakis, H. Sahli. Automatic Watershed segmentation of color images. In J. Goutsia, L. Vincent and Dan S. Bloomberg, editors, Mathematical Morphology and its applications on Image and Signal processing (ISMM’00), pp. 207–214. Kluwer Academic Press, 2000.Google Scholar
- 13.J. Weickert. Anisotropic Difusion in Image Processing ECMI Series, Teubner, Stuttgart, 1998.Google Scholar