NDLI: Clustering based image segmentation for elephant detection

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Clustering based image segmentation for elephant detection

Content Provider	IEEE Xplore Digital Library
Author	Vinod, S.T. Siva Mangai, N.M. Chandy, D.A.
Copyright Year	2014
Description	Author affiliation: Dept. of Electron. & Commun. Eng., Karunya Univ., Coimbatore, India (Vinod, S.T.; Siva Mangai, N.M.; Chandy, D.A.)
Abstract	This paper proposes a clustering based image segmentation approach for elephant recognition. Appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means algorithm employs the concept of fitness and belongingness to provide a more adaptive and betterclustering process as compared to several conventional algorithms. Elephant shape features are extracted for the recognition. Recognition rate for each class is calculated for performance evaluation. Recognition rate for different K values in K-NN classifier is calculated to find a proper K value for the proposed design.
Starting Page	1
Ending Page	5
File Size	820312
Page Count	5
File Format	PDF
e-ISBN	9781479923205
DOI	10.1109/ECS.2014.6892635
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-02-13
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis K-means Image segmentation Image recognition Databases KNN classifier Clustering algorithms Elephant Feature extraction Cameras Clustering Recognition
Content Type	Text
Resource Type	Article

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