Automatic individual identification of Saimaa ringed seals

• Published in: IET Computer Vision
• Main Authors: Tina Chehrsimin, Tuomas Eerola, Meeri Koivuniemi, Miina Auttila, Riikka Levänen, Marja Niemi, Mervi Kunnasranta, Heikki Kälviäinen
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2018
• Subjects: animal population monitoring; automatic image-based individual identification; endangered Saimaa ringed seal; Phoca hispida saimensis; distinctive permanent pelage pattern; seal segmentation; Computer applications to medicine. Medical informatics; R858-859.7; Computer software; QA76.75-76.765; Phoca hispida; ringed seal
• Online Access: https://doi.org/10.1049/iet-cvi.2017.0082; https://doaj.org/article/5fd92370644e45bc8b1e1516a6b58dcf

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.