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A biometric for shark dorsal fins based on boundary descriptor matching

9 pagesPublished: September 26, 2019

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.

Keyphrases: Biometric for sharks, Boundary descriptor, Minimum weight bipartite matching

In: Quan Yuan, Yan Shi, Les Miller, Gordon Lee, Gongzhu Hu and Takaaki Goto (editors). Proceedings of 32nd International Conference on Computer Applications in Industry and Engineering, vol 63, pages 63--71

Links:
BibTeX entry
@inproceedings{CAINE2019:biometric_for_shark_dorsal,
  author    = {Taina Coleman and Jucheol Moon},
  title     = {A biometric for shark dorsal fins based on boundary descriptor matching},
  booktitle = {Proceedings of 32nd International Conference on Computer Applications in Industry and Engineering},
  editor    = {Quan Yuan and Yan Shi and Les Miller and Gordon Lee and Gongzhu Hu and Takaaki Goto},
  series    = {EPiC Series in Computing},
  volume    = {63},
  pages     = {63--71},
  year      = {2019},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/1Rr8},
  doi       = {10.29007/bd51}}
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