A rule-based approach for robust clump splitting

This paper presents a robust rule-based approach for the splitting of binary clumps that are formed by objects of diverse shapes and sizes. First, the deepest boundary pixels, i.e., the concavity pixels in a clump, are detected using a fast and accurate scheme. Next, concavity-based rules are applie...

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Bibliographic Details
Published in:Pattern recognition 2006-06, Vol.39 (6), p.1088-1098
Main Authors: Kumar, S., Ong, S.H., Ranganath, S., Ong, T.C., Chew, F.T.
Format: Article
Language:English
Subjects:
Clump splitting
Concavity analysis
Overlapping objects
Segmentation
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Summary:This paper presents a robust rule-based approach for the splitting of binary clumps that are formed by objects of diverse shapes and sizes. First, the deepest boundary pixels, i.e., the concavity pixels in a clump, are detected using a fast and accurate scheme. Next, concavity-based rules are applied to generate the candidate split lines that join pairs of concavity pixels. A figure of merit is used to determine the best split line from the set of candidate lines. Experimental results show that the proposed approach is robust and accurate.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2005.11.014