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A Survey of Security Concerns in Various Data Aggregation Techniques in Wireless Sensor Networks Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Comparative Analysis of Cuckoo Search Optimization-Based Multilevel Image Thresholding

Authors : Sourya Roy, Utkarsh Kumar, Debayan Chakraborty, Sayak Nag, Arijit Mallick, Souradeep Dutta

Published in: Intelligent Computing, Communication and Devices

Publisher: Springer India

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Abstract

The entropy image thresholding technique is much in demand today for image segmentation. Furthermore, population algorithm aided thresholding techniques have been proven previously to be extremely effective in producing better results. In this work, we have concentrated on the minimum cross-entropy criterion for image segmentation. The objective of this work is to demonstrate the capability of Cuckoo Search Optimization-based Minimum Cross-Entropy Technique. The algorithm has been compared against old algorithms GA and PSO. Results have been assimilated in this work. The results have clearly demonstrated the competence of Cuckoo Search Optimization algorithm in assisting Cross Entropy-based thresholding procedure.

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previous chapter Unsupervised Segmentation of Satellite Images Based on Neural Network and Genetic Algorithm
next chapter An Intelligent Method for Moving Object Detection
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Metadata
Title
Comparative Analysis of Cuckoo Search Optimization-Based Multilevel Image Thresholding
Authors
Sourya Roy
Utkarsh Kumar
Debayan Chakraborty
Sayak Nag
Arijit Mallick
Souradeep Dutta
Copyright Year
2015
Publisher
Springer India
Book
Intelligent Computing, Communication and Devices

Print ISBN: 978-81-322-2008-4

Electronic ISBN: 978-81-322-2009-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-81-322-2009-1_38

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