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Computer Optics, 2016, Volume 40, Issue 6, Pages 904–910 (Mi co343)  

IMAGE PROCESSING, PATTERN RECOGNITION

An algorithm of image segmentation based on community detection in graphs

S. V. Belim, S. B. Larionov

F.M. Dostoevskiy Omsk State University, Omsk, Russia

Abstract: This article suggests an algorithm of image segmentation based on the community detection in graphs. The image is represented as a non-oriented weighted graph on which the community detection is carried out. Each pixel of the image is associated with a graph vertex. Only adjacent pixels are connected by edges. The weight of the edge is defined by subtracting the intensities of three color components of pixels. A Newman modularity function is used to check the quality of the graph partition into sub-graphs. It is suggested that a greedy algorithm should be applied to solving the image segmentation problem. Each community corresponds to a segment in the image. A computer experiment was carried out. The influence of the algorithm parameter to the segmentation results was revealed. The proposed algorithm was shown to be insensitive to random impulse noise.

Keywords: community detection, image segmentation.

DOI: https://doi.org/10.18287/2412-6179-2016-40-6-904-910

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Full text: http://www.computeroptics.smr.ru/.../400618.html
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Received: 06.04.2016
Accepted:07.09.2016

Citation: S. V. Belim, S. B. Larionov, “An algorithm of image segmentation based on community detection in graphs”, Computer Optics, 40:6 (2016), 904–910

Citation in format AMSBIB
\Bibitem{BelLar16}
\by S.~V.~Belim, S.~B.~Larionov
\paper An algorithm of image segmentation based on community detection in graphs
\jour Computer Optics
\yr 2016
\vol 40
\issue 6
\pages 904--910
\mathnet{http://mi.mathnet.ru/co343}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-6-904-910}


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