A fast level set method for propagating interfaces
Journal of Computational Physics
Digital image processing
Accelerating exact k-means algorithms with geometric reasoning
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
SIAM Review
A remark on computing distance functions
Journal of Computational Physics
Rapid and accurate computation of the distance function using grids
Journal of Computational Physics
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
IEEE Transactions on Image Processing
Intelligent segmentation method for real-time defect inspection system
Computers in Industry
Context-aware volume modeling of skeletal muscles
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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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.