Title: EyeRIS: image-based identification of goats using Iris

Authors: Satyendra Nath Mandal; Subhranil Mustafi; Sanket Dan; Pritam Ghosh; Dilip Kumar Hajra; Santanu Banik; Shyamal Naskar

Addresses: Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, 741235, India ' DST-INSPIRE Fellow, CVPR Unit, Indian Statistical Institute, Kolkata, West Bengal 700108, India ' Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, 741235, India ' Department of Computer Science & Technology, Iswar Chandra Vidyasagar Polytechnic, Jhargram, West Bengal, 721514, India ' Department of Agronomy, Uttar Banga Krishi Vishwavidyalaya, Pundibari, West Bengal, 736165, India ' Principal Scientist (Animal Genetics and Breeding), ICAR-National Research Centre on Pig, Rani, Assam, 781015, India ' ICAR – Indian Veterinary Research Institute, Kolkata, West Bengal, 700037, India

Abstract: Existing identification systems for goats are physically tamperable and thus a biometric system needs to be developed to overcome such. After image acquisition through single lens reflex (SLR) camera, the iris potion is segmented using snake contouring, normalised and feature encoded leading to the generation of templates. The matching between such stored and query templates using the metric of hamming distance develops a specific threshold, wherein the values less than it claim to be of the same individual and vice versa for different individual goats. During this experimentation, the recognition of black Bengal goats using iris patterns has been established as a unique and viable trait. Later, it has been extrapolated to the other five breeds named Jamunapuri, Sirohi, Beetal, Jakhrana, and Barbari. The accuracy has been found to be 98%, better than that of different technologies for identification of animals, keeping the time complexity under prime consideration.

Keywords: goat Aadhaar; log Gabor filter; convolution; template generation; hamming distance.

DOI: 10.1504/IJCBDD.2023.134616

International Journal of Computational Biology and Drug Design, 2023 Vol.15 No.6, pp.480 - 502

Accepted: 01 May 2023
Published online: 31 Oct 2023 *

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