A rule-based approach for robust clump splitting

  • Authors:

  • S. Kumar;S. H. Ong;S. Ranganath;T. C. Ong;F. T. Chew

  • Affiliations:

  • Department of Electrical and Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore and Division of Bioengineering, National University of Sing ...;Department of Electrical and Computer Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;Department of Biological Sciences, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;Department of Biological Sciences, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore

  • Venue:
  • Pattern Recognition
  • Year:
  • 2006

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Abstract

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.