Graph-based image segmentation using k-means clustering and normalised cuts

Chong, Mei Yeen and Khong, Wei Leong and Kow, Wei Yeang and Lorita Angeline, and Teo, Kenneth Tze Kin (2012) Graph-based image segmentation using k-means clustering and normalised cuts. In: 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012, 24-26 July 2012, Phuket, Thailand.

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Official URL: http://dx.doi.org/ 10.1109/CICSyN.2012.64

Abstract

Image segmentation with low computational burden has been highly regarded as important goal for researchers. Various image segmentation methods are widely discussed and more noble segmentation methods are expected to be developed when there is rapid demand from the emerging machine vision field. One of the popular image segmentation methods is by using normalised cuts algorithm. It is unfavourable for a high resolution image to have its resolution reduced as high detail information is not fully made used when critical objects with weak edges is coarsened undesirably after its resolution reduced. Thus, a graph-based image segmentation method done in multistage manner is proposed here. In this paper, an experimental study based on the method is conducted. This study shows an alternative approach on the segmentation method using k-means clustering and normalised cuts in multistage manner.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Image segmentation, k-means clustering, Normalised cuts
Subjects:?? TA1501-1820 ??
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:5296
Deposited By:IR Admin
Deposited On:01 Nov 2012 15:10
Last Modified:08 Sep 2014 12:49

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