Skip to main content

Research Repository

Advanced Search

Biometric cattle identification approach based on Weber's local descriptor and AdaBoost classifier

Gaber, T; Tharwat, A; Hassanien, AE; Snasel, V

Biometric cattle identification approach based on Weber's local descriptor and AdaBoost classifier Thumbnail


Authors

T Gaber

A Tharwat

AE Hassanien

V Snasel



Abstract

In this paper, we proposed a new and robust biometric-based approach to identify head of cattle. This approach used the Weber Local Descriptor (WLD) to extract robust features from cattle muzzle print images (images from 31 head of cattle were used). It also employed the AdaBoost classifier to identify head of cattle from their WLD features. To validate the results obtained by this classifier, other two classifiers (k-Nearest Neighbor (k-NN) and Fuzzy-k-Nearest Neighbor (Fk-NN)) were used. The experimental results showed that the proposed approach achieved a promising accuracy result (approximately 99.5%) which is better than existed proposed solutions. Moreover, to evaluate the results of the proposed approach, four different assessment methods (Area Under Curve (AUC), Sensitivity and Specificity, accuracy rate, and Equal Error Rate (EER)) were used. The results of all these methods showed that the WLD along with AdaBoost algorithm gave very promising results compared to both of the k-NN and Fk-NN algorithms.

Citation

Gaber, T., Tharwat, A., Hassanien, A., & Snasel, V. (2016). Biometric cattle identification approach based on Weber's local descriptor and AdaBoost classifier. Computers and Electronics in Agriculture, 122, https://doi.org/10.1016/j.compag.2015.12.022

Journal Article Type Article
Acceptance Date Dec 31, 2015
Online Publication Date Jan 25, 2016
Publication Date Mar 1, 2016
Deposit Date Aug 19, 2019
Publicly Available Date Aug 19, 2019
Journal Computers and Electronics in Agriculture
Print ISSN 0168-1699
Electronic ISSN 1872-7107
Publisher Elsevier
Volume 122
DOI https://doi.org/10.1016/j.compag.2015.12.022
Publisher URL https://doi.org/10.1016/j.compag.2015.12.022
Related Public URLs https://www.sciencedirect.com/journal/computers-and-electronics-in-agriculture

Files






You might also like



Downloadable Citations