In this paper we present a new approach inorder to develop a robust segmentation algorithm taking into account perceptual features of the Human Visual System (HVS). Many segmentation methods show some weaknesses to deal with irrelevant or irregular textured regions. Through a watershed transform, we propose to extend the well-known segmentation algorithm JSEG. weighting the J criterion with the distance between the colour of the processed pixel and the mean perceived colour at a selected scale. This is defined by the colour information perceived by the HVS when the distance from the observer to the image grows up. We combine J criterion and colour gradient and show how to improve this by removing the irrelevant detection of chaotic texture patterns. These patterns appear mainly on natural scene, in objects like grass or hairs, and on noised regions which produce unwanted texture breaks.
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