Image segmentation using a generalized fast level set method

Authors:
Dang Tran Vu;Jin Young Kim;Seung Ho Choi;Seung You Na
Affiliations:
School of Electronics & Computer Engineering, Chonnam National University;School of Electronics & Computer Engineering, Chonnam National University;Dept. of Computer Eng., Dongshin University;School of Electronics & Computer Engineering, Chonnam National University
Venue:
ISPRA'10 Proceedings of the 9th WSEAS international conference on Signal processing, robotics and automation
Year:
2010

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Abstract

Image segmentation is one of the most important and fundamental tasks in image processing. In this paper we address the drawbacks of the previous level set methods for segmentation problems and propose a Generalized Fast Level Set Method to cope with the limitations. We formulate a new level set function, study its stability, introduce a relationship matrix, a modified Chan-Vese model and a novel filtering criterion to construct a novel and effective segmentation technique. The experimental results show that this technique can be used in segmenting individual objects or individual parts of an object in images, which is useful in reducing the heavy image noises. These results also demonstrate that the proposed method is more effective and efficient than the classical Level Set Methods and the original Fast Level Set Method.