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Scientific Programming
Volume 12 (2004), Issue 2, Pages 101-120

Efficient Active Contour and K-Means Algorithms in Image Segmentation

J.R. Rommelse,1 H.X. Lin,1 and T.F. Chan2

1Department of Applied Mathematical Analysis, Delft University of Technology, Delft, 2628 CD, The Netherlands
2Department of Mathematics, University of California, Los Angeles Los Angeles, CA 90095-1555, USA

Received 19 July 2004; Accepted 19 July 2004

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed active contour image segmentation model. We propose integrating aspects of the classic algorithm to improve the active contour model. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.