IET Computer Vision (Mar 2018)

Automatic individual identification of Saimaa ringed seals

  • Tina Chehrsimin,
  • Tuomas Eerola,
  • Meeri Koivuniemi,
  • Miina Auttila,
  • Riikka Levänen,
  • Marja Niemi,
  • Mervi Kunnasranta,
  • Heikki Kälviäinen

DOI
https://doi.org/10.1049/iet-cvi.2017.0082
Journal volume & issue
Vol. 12, no. 2
pp. 146 – 152

Abstract

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In order to monitor an animal population and to track individual animals in a non‐invasive way, identification of individual animals based on certain distinctive characteristics is necessary. In this study, automatic image‐based individual identification of the endangered Saimaa ringed seal (Phoca hispida saimensis) is considered. Ringed seals have a distinctive permanent pelage pattern that is unique to each individual. This can be used as a basis for the identification process. The authors propose a framework that starts with segmentation of the seal from the background and proceeds to various post‐processing steps to make the pelage pattern more visible and the identification easier. Finally, two existing species independent individual identification methods are compared with a challenging data set of Saimaa ringed seal images. The results show that the segmentation and proposed post‐processing steps increase the identification performance.

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