A Novel Marker Based Interactive Image Segmentation Method

An important branch of computer vision is image segmentation. Image segmentation aims at extracting meaningful objects lying in images either by dividing images into contiguous semantic regions, or by extracting one or more specific objects in images such as medical structures. The image segmentation task is in general very difficult to achieve since natural images are diverse, complex and the way we perceive them vary according to individuals. For more than a decade, a promising mathematical framework, based on variational models and partial differential equations, have been investigated to solve the image segmentation problem. The proposed scheme is simple yet powerful and it is image content adaptive. With the similarity based merging rule, a two stage iterative merging algorithm was presented to gradually label each non-marker region as either object or background. We implemented the MSRM algorithm in the MATLAB.

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