A Cattle Identification Approach Using Live Captured Muzzle Print Images

Ali Ismail Awad, Aboul Ella Hassanien, Hossam M. Zawbaa

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

20 Citations (Scopus)

Abstract

Cattle identification receives a great research attention as a dominant 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 approach from live captured muzzle print images with local invariant features. The presented approach compensates some weakness of traditional cattle identification schemes in terms of accuracy and processing time. The proposed scheme uses Scale Invariant Feature Transform (SIFT) for detecting the interesting points for image matching. In order to enhance the robustness of the presented technique, 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 approach because it achieves 93.3% identification accuracy in reasonable processing time compared to 90% identification accuracy achieved by some other reported approaches.

Original languageEnglish
Title of host publicationAdvances in Security of Information and Communication Networks - 1st International Conference, SecNet 2013, Proceedings
PublisherSpringer Verlag
Pages143-152
Number of pages10
ISBN (Print)9783642405969
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event1st International Conference on Advances in Security of Information and Communication Networks, SecNet 2013 - Cairo, Egypt
Duration: Sept 3 2013Sept 5 2013

Publication series

NameCommunications in Computer and Information Science
Volume381 CCIS
ISSN (Print)1865-0929

Conference

Conference1st International Conference on Advances in Security of Information and Communication Networks, SecNet 2013
Country/TerritoryEgypt
CityCairo
Period9/3/139/5/13

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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