Performance Analysis of Clustering Techniques for Object Oriented Segmentation of Satellite Images

Bharathi Somashekhar, . and Pooja P Sheth, . and Venugopal, K.R. and Patnaik, L.M. and Deepa Shenoy, P. (2010) Performance Analysis of Clustering Techniques for Object Oriented Segmentation of Satellite Images. In Proc. of International Conference on Information Processing.

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Abstract

This paper presents a new approach for color based image segmentation by applying Fuzzy c-means algorithm. This segmentation process includes a new mechanism for clustering the elements of high –resolution images in order to improve precision and reduce computation time. Normally, due to the progress in spatial resolution of satellite imagery, the methods of segment-based image analysis for Fuzzy c-means (FCM) clustering is one of well-known unsupervised clustering techniques, which can be used for unsupervised image segmentation. The measurement data considered from an unsupervised fuzzy clustering technique is only used to reveal the underlying structure of the data and segment the image in regions with similar spectral properties. So this method has not relationship between

Item Type: Article
Subjects: Faculty of Engineering > Computer Science & Information Science Engineering
Divisions: University Visvesvarayya College of Engineering > Department of Computer Science and Information Science Engineering
Depositing User: Ms. Shwetha A C
Date Deposited: 22 Oct 2021 06:02
Last Modified: 22 Oct 2021 06:02
URI: http://eprints-bangaloreuniversity.in/id/eprint/10225

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