Automatic individual identification of Saimaa ringed seals

• Published in: IET Computer Vision
• Main Authors: Chehrsimin, Tina, Eerola, Tuomas, Koivuniemi, Meeri, Auttila, Miina, Levänen, Riikka, Niemi, Marja, Kunnasranta, Mervi, Kälviäinen, Heikki
• Other Authors: Machine Vision and Pattern Recognition Laboratory, School of Engineering Science, Lappeenranta University of Technology, Department of Environmental and Biological Sciences, University of Eastern Finland, Parks & Wildlife Finland, State Forest Enterprise (Metsähallitus), Luke / Luonnonvarat ja biotuotanto / Riista- ja kalavarat / Riistavarat (4100100513), 4100100513
• Format: Article in Journal/Newspaper
• Language: English
• Published: The Institute of Engineering and Technology, IET
• Subjects: seals; Pusa hispida; endangered Saimaa ringed seal; Phoca hispida saimensis; automatic image-based individual identification; animal population monitoring; segmentation; distinctive permanent pelage pattern; Phoca hispida; ringed seal
• Online Access: http://jukuri.luke.fi/handle/10024/541067

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 postprocessing 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. 2017