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[SourceCode] Image Segmentation Using Iterative Watersheding DL : 0: This paper presents a novel segmentation algorithm for metallographic images, especially those objects without regular boundaries and homogeneous intensity. In metallographic quantification, the complex microstructures make the conventional approaches hard to achieve a satisfactory partition. We formulate the segmentation procedure as a new framework of iterative watershed region growing constrained by the ridge information. The seeds are selected by an effective double-threshold approach, and the ridges are superimposed as the highest waterlines in watershed transform. To tackle the over-segmentation problem, the blobs are merged iteratively with the utilization of Bayes classification rule. Experimental results show that the algorithm is effective in performing segmentation without too much parameter tuning.
Date : 2011-05-05 Size : 695.57kb User : jjrs05