Abstract
The aim in this paper is to present a graph-based method for image processing from color digital images and to extract their color and geometric features, in order to determine later the contours of the visual objects and to perform syntactic analysis of the determined shapes. This method may be extended for volumetric digital images. The proposed graph-based segmentation method is divided into two different steps: (a) a step that produces a maximum spanning tree of the connected components of the virtual triangular grid graph constructed on the hexagonal structure of the input image, and (b) the final segmentation step that produces a minimum spanning tree of the connected components, representing the visual objects, by using dynamic weights based on the geometric features of the regions. The first step uses only color information extracted from RGB input image, whereas the final segmentation step uses both color and geometric and configuration of image regions.
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