Open AccessAutomatic individual identification of Saimaa ringed seals
Author(s) -
Chehrsimin Tina,
Eerola Tuomas,
Koivuniemi Meeri,
Auttila Miina,
Levänen Riikka,
Niemi Marja,
Kunnasranta Mervi,
Kälviäinen Heikki
Publication year - 2018
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2017.0082
Subject(s) - identification (biology) , phoca , computer science , segmentation , population , artificial intelligence , process (computing) , seal (emblem) , pattern recognition (psychology) , set (abstract data type) , image segmentation , computer vision , ecology , geography , biology , demography , archaeology , sociology , programming language , operating system
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.