Efficient active contour and K-means algorithms in image segmentation

Issue title: Distributed Computing and Applications

Article type: Research Article

Authors: Rommelse, J.R.^; | Lin, H.X.^; | Chan, T.F.

Affiliations: Department of Applied Mathematical Analysis, Delft University of Technology, Delft, 2628 CD, The Netherlands | E-mail: J.R.Rommelse@ewi.tudelft.nl | E-mail: H.X.Lin@ewi.tudelft.nl | Department of Mathematics, University of California, Los Angeles Los Angeles, CA 90095-1555, USA. E-mail: Chan@math.ucla.edu

Abstract: 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.

Keywords: image segmentation, clustering algorithm, active contour model, level set functions, synchronous and asynchronous communication

Journal: Scientific Programming, vol. 12, no. 2, pp. 101-120, 2004