A biometric for shark dorsal fins based on boundary descriptor matching
26. September 2019
A biometric for shark dorsal fins based on boundary descriptor matching
Taina Coleman and Jucheol Moon
ABSTRACT:
Recent progress in animal biometrics has revolutionized wildlife research. Cutting edge techniques allow researchers to track individuals through noninvasive methods of recognition that are not only more reliable, but also applicable to large, hard-to-find, and otherwise difficult to observe animals. In this research, we propose a metric for boundary descriptors based on bipartite perfect matching applied in shark dorsal fins. In order to identify a shark, we first take a fin contour and transform it to a normalized coordinate system so that we can analyze images of sharks regardless of orientation and scale. Finally, we propose a metric scheme that performs a minimum weight perfect matching in a bipartite graph. The experimental results show that our metric is applicable to identify and track individuals from visual data.
EPiC Series in Computing, Volume 63, 2019, Pages 63–71, DOI 10.29007/bd51