Automatic individual identification of Saimaa ringed seals
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2017Author(s)
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10.1049/iet-cvi.2017.0082Metadata
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Chehrsimin Tina. Eerola Tuomas. Koivuniemi Meeri. Auttila Miina. Levänen Riikka. Niemi Marja. Kunnasranta Mervi. Kälviäinen Heikki. (2017). Automatic individual identification of Saimaa ringed seals. IET Computer Vision, [Available online 24 Oct 2017 ], 10.1049/iet-cvi.2017.0082.Rights
Abstract
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.