Color image segmentation guided by a color gradient network

Authors:
Aldo v. Wangenheim;Rafael F. Bertoldi;Daniel D. Abdala;Michael M. Richter
Affiliations:
Image Processing and Computer Graphics Lab - LAPIX, CS Department, Federal University of Santa Catarina - UFSC, Florianópolis, SC, Brazil;Image Processing and Computer Graphics Lab - LAPIX, CS Department, Federal University of Santa Catarina - UFSC, Florianópolis, SC, Brazil;Computer Vision and Pattern Recognition Group, University Münster, Münster, Germany;CS Department, University of Calgary, Calgary, Alberta, Canada
Venue:
Pattern Recognition Letters
Year:
2007

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Abstract

Existing region-growing segmentation algorithms are mainly based on a static similarity concept, where only homogeneity of pixels or textures within a region plays a role. Typical natural scenes, however, show strong continuous variations of color, presenting a different, dynamic order that is not captured by existing algorithms which will segment a sky with different intensities and hues of blues or an irregularly illuminated surface as a set of different regions. We present and validate empirically a new, extremely simple approach that shows very satisfying results when applied on such scenes, while not showing poorer performance than traditional methods when applied to standard region-growing problems.