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Optical Engineering

Merging toward natural clusters
Author(s): Zhigang Tan; Nelson Hon Ching Yung
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Paper Abstract

To findout how many clusters exist in a sample set is an old yet unsolved problem in unsupervised clustering. This problem inevitably occurs in region merging/growing, a well studied and popular technique in image segmentation. Region merging usually needs a stop criterion. The stop criterion is not automatically determined and often has to be set manually to arrive at a sensible segmentation, which is rather difficult for natural images. To address this problem, we present a robust stop criterion that is based on a novel distinctness predicate for adjacent regions. The predicate discerns distinct regions by examining the evidence of the boundary between neighboring regions. Requiring that every region should be distinct from each other, the proposed method is able to choose a stop point where a natural partition is most likely. Under a region merging framework, we demonstrate the effectiveness of the stop criterion using two merging criterion: one based on optimizing a global functional, and another based on a local criterion. Experimental results and comparison are given at the end.

Paper Details

Date Published: 1 July 2009
PDF: 14 pages
Opt. Eng. 48(7) 077202 doi: 10.1117/1.3183892
Published in: Optical Engineering Volume 48, Issue 7
Show Author Affiliations
Zhigang Tan, The Univ. of Hong Kong (Hong Kong, China)
Nelson Hon Ching Yung, The Univ. of Hong Kong (Hong Kong, China)

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