A novel method for splitting clumps of convex objects incorporating image intensity and using rectangular window-based concavity point-pair search

Authors:
Muhammad Farhan;Olli Yli-Harja;Antti Niemistö
Affiliations:
Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere, Finland;Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere, Finland;Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere, Finland
Venue:
Pattern Recognition
Year:
2013

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Abstract

A novel nonparametric concavity point analysis-based method for splitting clumps of convex objects in binary images is presented. The method is based on finding concavity point-pairs by using a variable-size rectangular window. The concavity point-pairs can be either connected with a straight split line or with a line that follows a path of minimum or maximum intensity on an accompanying grayscale image. Using straight lines can result in non-smooth contours. Therefore, post-processing steps that remove acute angles between split lines are proposed. Results obtained with images that have clumps of biological cells show that the method gives accurate results.