Fish Detection and Measurement based on Mask R-CNN

  • Wan Song Rocha UNIR
  • Carolina Rodrigues da Costa Doria UNIR
  • Carolina Yukari Veludo Watanabe UNIR

Abstract


Morphological measurements of fish, extracted from their contour, are essential indicators, with applications in the fishing industry as well as for monitoring and preserving species. Thus, automatic contour extraction techniques have been explored, and the development of methods for segmenting fish images is necessary. Therefore, the goal of this work was to develop an approach to automatically measure the length of the fish, using the Mask R-CNN network in the fish segmentation task. Comparing the fish length measurements of the proposed method with the size performed manually, an average relative error of only 2.26% was obtained. Thus, a system for automating this process can be faster, more productive, and more scalable.

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Published
2020-11-07
ROCHA, Wan Song; DORIA, Carolina Rodrigues da Costa; WATANABE, Carolina Yukari Veludo. Fish Detection and Measurement based on Mask R-CNN. In: WORKSHOP OF UNDERGRADUATE WORKS - CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 33. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 183-186. DOI: https://doi.org/10.5753/sibgrapi.est.2020.13007.