Color image segmentation guided by a color gradient network

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.