Affiliation:
1. Institute of Cybernetics "E.Caianiello", National Research Council of Italy, Via Campi Flegrei 34 — 80078 Pozzuoli, Napoli, Italy
Abstract
The watershed transformation is a primary tool for segmenting a grey-tone image into subsets that are of interest to a visual observer. The resulting image, however, may often appear oversegmented into a large number of tiny regions (basins), most of which are not significant to the problem of domain. In this paper, a method for removing these nonsignificant basins is presented. The notions of relative significance and intrinsic significance are introduced, which lead to the definition of three types of significance for a basin: strong, weak and partial. The merging of a basin with other basins only occurs when the significance of the basin is not strong, and is restricted to suitably selected adjacent basins. The merging is performed by using an iterated process consisting of two phases. The first involves the removal of certain regional minima, and is accomplished by following either a flooding or a digging scheme. The second identifies the basins corresponding to the regional minima remaining in the image and utilizes the watershed transformation. An appropriate selection of the basins to be merged produces a segmented image perceptually close to the original image. The performance of the proposed method is for the case of astronomic images.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
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