A robust cattle identification scheme using muzzle print images

Ali Ismail Awad, Hossam M. Zawbaa, Hamdi A. Mahmoud, Eman Hany Hassan Abdel Nabi, Rabie Hassan Fayed, Aboul Ella Hassanien

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Citations (Scopus)

Abstract

Cattle identification receives a great research attention as an important way to maintain the livestock. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle print images using local invariant features. The presented scheme compensates some weakness of ear tag and electrical-based traditional identification techniques in terms of accuracy and processing time. The proposed scheme uses Scale Invariant Feature Transform (SIFT) for detecting the interesting points for image matching. For a robust identification scheme, a Random Sample Consensus (RANSAC) algorithm has been coupled with the SIFT output to remove the outlier points and achieve more robustness. The experimental evaluations prove the superiority of the presented scheme as it achieves 93.3% identification accuracy in reasonable processing time compared to 90% identification accuracy achieved by some traditional identification approaches.

Original languageEnglish
Title of host publication2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013
Pages529-534
Number of pages6
Publication statusPublished - 2013
Externally publishedYes
Event2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013 - Krakow, Poland
Duration: Sept 8 2013Sept 11 2013

Publication series

Name2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013

Conference

Conference2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013
Country/TerritoryPoland
CityKrakow
Period9/8/139/11/13

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems

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