This work introduces Jmin-images as an alternative to gradient maps in watershed-based image segmentation algorithms. A Jmin-image is computed using J-images that are color-texture homogeneity maps based on Fisher’s discriminant, introduced in [1]. The major advantage of using Jmin is the elimination of the scale selection problem for texture segmentation. A filtered Jmin is used as input for a watershed algorithm whose output is refined by a color histogram based hierarchical clustering step. Experimental results show good performance in the segmentation of natural images.
BibTeX
@article{Santos:ISMM2007,
title = {Jmin-image based color-texture segmentation using watershed and hierarchical clustering},
author = {Thiago T. Santos and Carlos H. Morimoto and Rama Chellappa},
journal = {Proceedings of the 8th International Symposium on Mathematical Morphology},
address = {Rio de Janeiro, Brazil},
month = {October},
pages = {35-36},
year = {2007},
volume = {2},
}