Abstract
The level set method has many advantages for image segmentation, such as dealing with sharp corners, segmenting the boundaries of complex object and so on. However, it is easily affected by initial contour and control parameters. Fuzzy C-Means (FCM) clustering algorithm is one of the most popular methods of clustering analysis. Nevertheless, the traditional FCM clustering algorithm does not work well, because its initial centers are chosen randomly. In this paper, with the help of Genetic Algorithm (GA), we get the optimized cluster centers. For images, the resulting fuzzy clustering is used as the initial level set contour. At the same time, the results of fuzzy clustering can reduce the controlling parameters of level set method. The experiment results confirm its advantages for image segmentation.
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