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Genetic cuts for image segmentation

[+] Author Affiliations
Shiueng-Bien Yang

Wenzao Ursuline University of Languages, Department of Digital Content Application and Management, 900 Mintsu 1st Road Kaohsing 80424, Taiwan

J. Electron. Imaging. 23(5), 053024 (Oct 27, 2014). doi:10.1117/1.JEI.23.5.053024
History: Received January 19, 2014; Revised September 13, 2014; Accepted October 1, 2014
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Abstract.  The normalized cut (Ncut) method is a popular method for segmenting images and videos. The Ncut method segments an image into two disjoint regions, each segmented by the same method. After the Ncut method has been recursively applied to an image, its final segmented image is obtained. The main drawback of the Ncut method is that a user cannot easily determine the stop criteria because users have no idea about the number of regions in an image. This work proposes the genetic cut (Gcut) algorithm to resolve this shortcoming. Users do need not to specify thresholds in the Gcut algorithm, which automatically segments an image into the proper number of regions. Also, the neighbor-merging (NM) algorithm is proposed for preprocessing the images and improves the performance of the Gcut algorithm. Thus, the proposed Gcut method combines the NM and Gcut algorithms. Furthermore, a heuristic method is proposed to identify a good segment for the Gcut method. In all experiments, the proposed Gcut method outperforms traditional Ncut methods.

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Citation

Shiueng-Bien Yang
"Genetic cuts for image segmentation", J. Electron. Imaging. 23(5), 053024 (Oct 27, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.5.053024


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