Normalized cut segmentation was introduced by Jianbo shi and Jitendra Malik. They published a paper “Normalized Cuts and Image Segmentation” in 2000 (Journal IEEE Transaction on pattern Analysis and machine Intelligence volume 22 Issue 8, August 2000) Here they have proposed a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, their approach aims at extracting the global impression of an image. This algorithm treat image segmentation as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. And also they have proposed an efficient computational technique based on a generalized eigenvalue problem which can be used to optimize this criterion. This project is a Matlab implementation of that segmentation method.
