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Two-Stage/Three-Stage Method for Image Segmentation

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VMVW03 - Flows, mappings and shapes

The Mumford–Shah model is one of the most important image segmentation models and has been studied extensively in the last twenty years. In this talk, we propose a two-stage segmentation method based on the Mumford–Shah model. The first stage of our method is to find a smooth solution to a convex variant of the Mumford–Shah model. In the second stage the segmentation is done by thresholding the previous image into different phases. Experimental results show the good performance of the proposed method. The idea is then generalized for image segmentation under non-Gaussian noise, color image segmentation and selective image segmentation for medical images.

This talk is part of the Isaac Newton Institute Seminar Series series.

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