Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions

Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7540

Title:	Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions
Authors:	Bhandari A.K. Kumar A. Singh, Girish Kumar
Published in:	Expert Systems with Applications
Abstract:	In this paper, a modified artificial bee colony (MABC) algorithm based satellite image segmentation using different objective function has been presented to find the optimal multilevel thresholds. Three different methods are compared with this proposed me
Citation:	Expert Systems with Applications (2015), 42(3): 1573-1601
URI:	https://doi.org/10.1016/j.eswa.2014.09.049 http://repository.iitr.ac.in/handle/123456789/7540
Issue Date:	2015
Publisher:	Elsevier Ltd
Keywords:	ABC Between-class variance Image segmentation Kapur's entropy MABC Multilevel thresholding PSO and GA algorithm Tsallis entropy
ISSN:	9574174
Author Scopus IDs:	25651606700 35220209900 57193351909
Author Affiliations:	Bhandari, A.K., PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur, 482005, India Kumar, A., PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur, 482005, India Singh, G.K., Department of Ele
Corresponding Author:	Bhandari, A.K.; PDPM Indian Institute of Information Technology Design and ManufacturingIndia
Appears in Collections:	Journal Publications [EE]

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