Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2010.1073
Title: A recursive and model-constrained region splitting algorithm for cell clump decomposition
Authors: Xiong, W.
Ong, S.H. 
Lim, J.H.
Issue Date: 2010
Source: Xiong, W.,Ong, S.H.,Lim, J.H. (2010). A recursive and model-constrained region splitting algorithm for cell clump decomposition. Proceedings - International Conference on Pattern Recognition : 4416-4419. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2010.1073
Abstract: Decomposition of cells in clumps is a difficult segmentation task requiring region splitting techniques. Techniques that do not employ prior shape constraints usually fail to achieve accurate segmentation. Those using shape constraints are unable to cope with large clumps and occlusions. In this work, we propose a model-constrained region splitting algorithm for cell clump decomposition. We build the cell model using joint probability distribution of invariant shape features. The shape model, the contour smoothness and the gradient information along the cut are used to optimize the splitting in a recursive manner. The short cut rule is also adopted as a strategy to speed up the process. The algorithm performs well in validation experiments using 60 images with 4516 cells and 520 clumps. © 2010 IEEE.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/69037
ISBN: 9780769541099
ISSN: 10514651
DOI: 10.1109/ICPR.2010.1073
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