A De-Texturing and Spatially-Constrained K-Means Approach For Image Segmentation

Max Mignotte
DIRO, Département d'Informatique et de Recherche Opérationnelle, CP 6128,
Succ. Centre-Ville, P.O. 6128, Montréal (Québec), H3C 3J7.


ABSTRACT

In this work, we present a new and simple segmentation method based only on the k-means clustering procedure and a two-step process. The first step relies on a original de-texturing procedure which aims at converting the input natural textured color image into a color image without texture, which will then be easier to segment. Once, this de-textured (color) image is estimated, a final segmentation is achieved by a K-means segmentation.


SEGMENTATION RESULTS