Automatic live fingerlings counting using computer vision

Pedro Lucas França Albuquerque, Vanir Garcia, Adair da Silva Oliveira, Tiago Lewandowski, Carrick Detweiler, Ariadne Barbosa Gonçalves, Celso Soares Costa, Marco Hiroshi Naka, Hemerson Pistori

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Fish counting is still a rudimentary process in most fisheries in Brazil. Current solutions are generally unaffordable for small and medium-size producers; hence, in order to provide a low-cost solution, this paper proposes a new technique for fish counting and presents a new image dataset to evaluate fish counting systems. The dataset is composed of a series of videos partially annotated at frame-level, which include approximately a thousand fish in high-resolution images. We describe a computer-vision based system that counts fish by combining information from blob detection, mixture of Gaussians and a Kalman filter. This work shows that the proposed method is a feasible approach for automatic fish counting, reducing costs and boosting production, as it increases labor availability. Our approach is efficient for fingerlings counting, with an average precision of 97.47%, recall of 97.61% and F-measure of 97.52% in the provided dataset.

Original languageEnglish (US)
Article number105015
JournalComputers and Electronics in Agriculture
StatePublished - Dec 2019


  • Aquaculture
  • Computer vision
  • Fish counting
  • Fish farming

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture


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