Title: Recognition of elephants in infrared images using clustering-based image segmentation

Authors: N.M. Siva Mangai; Shilu Tresa Vinod; D. Abraham Chandy

Addresses: Department of Electronics and Communication Engineering, Karunya University, Coimbatore, TamilNadu, India ' Department of Electronics and Communication Engineering, Karunya University, Coimbatore, TamilNadu, India ' Department of Electronics and Communication Engineering, Karunya University, Coimbatore, TamilNadu, India

Abstract: Object recognition is a challenging task in image processing and computer vision. This paper proposes a clustering-based image segmentation approach for elephant recognition. An appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means clustering algorithm employs the concept of fitness and belongingness to provide a more adaptive and better clustering process as compared to several conventional algorithms. Elephant shape features are extracted for the recognition. The recognition rate for each class is calculated for performance evaluation. The recognition rate for different K values in K-NN classifier is calculated to find a proper K value for the proposed design.

Keywords: elephants; elephant recognition; object recognition; image segmentation; K-nearest neighbour; k-means clustering; shape features; feature extraction; KNN classifier.

DOI: 10.1504/IJESDF.2015.070390

International Journal of Electronic Security and Digital Forensics, 2015 Vol.7 No.3, pp.234 - 244

Received: 03 Jul 2014
Accepted: 04 Dec 2014
Published online: 04 Jul 2015 *

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