Assessment of retinal recognition technology as a biometric method for sheep identification

Authors:
U. Gonzales Barron;G. Corkery;B. Barry;F. Butler;K. McDonnell;S. Ward
Affiliations:
Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland;Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland;Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland;Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland;Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland;Biosystems Engineering, School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Dublin, Ireland
Venue:
Computers and Electronics in Agriculture
Year:
2008

Citing 1
Cited 5

Information fusion in biometrics

Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)

Original papers: A longitudinal study of the effect of time on the matching performance of a retinal recognition system for lambs

Computers and Electronics in Agriculture
A framework for beef traceability from farm to slaughter using global standards: An Irish perspective

Computers and Electronics in Agriculture
A preliminary in vivo study on the potential application of e-tracking in poultry using ink printed 2D barcodes

Computers and Electronics in Agriculture
A bivariate model for retinal image identification in lambs

Computers and Electronics in Agriculture
A new cow identification system based on iris analysis and recognition

International Journal of Biometrics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In order to assure effective traceability, food-producing animals must be identified by a tamper-proof and durable technique. With the advance in human biometric technologies, the deployment of retinal recognition technology for cattle identification and verification has been prompted. The objective of this study was to assess the accuracy of a commercially available retina biometric technology for sheep identification (i) by determining whether light conditions during retinal image capture (indoors and outdoors with shade) and different operators exerted any significant effect on the matching score of the built-in pattern matching algorithm; and (ii) by evaluating the recognition performance of the biometric system for enrolment of one retinal image per sheep and two retinal images per sheep (bimodal biometric system). Neither the light conditions nor the operators were found to have a statistically significant effect on the matching score values of the built-in algorithm; yet it was clear that the pupillary light reflex phenomenon played a major role in obtaining lower matching score values for retinal images taken outdoors. The recognition errors of the one-retina biometric system were estimated to be 0.25% for false matches and 0.82% for false non-matches. An improved bimodal biometric system, i.e., two retinas, that applies a decision criterion based on a simple OR logical operator and a sum of matching scores, has been proposed in this study in order to reduce both probabilities of false matches and false non-matches to near zero.