Shrimp Shape Analysis by a Chord Length Function Based Methodology

Fernando J. Ramírez-Coronel, Oscar M. Rodríguez-Elías*, Madaín Pérez-Patricio, Edgard Esquer-Miranda, Julio Waissman-Vilanova, Mario I. Chacón-Murguía, Omar Hernández-González

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The most expensive operational cost in shrimp farming and in every aquaculture system is feeding. To estimate the quantity of food is necessary to know the total biomass of the pond. Traditionally, this is done by taking samples and weighting, which is invasive and stress the animals. Non intrusive methods have been tried to estimate pond biomass using different technologies, being one of them computer vision. Computer vision faces several challenges, such as the problem of how to identify shrimps, count them, estimate their size and their mass. In this work, a chord length function based methodology is proposed as a viable alternative to analyze shrimp’s shape and count them, this methodology generates histograms of the shape of the shrimps and therefore, a set of statistical parameters (mean, median, mode, variance, standard deviation, maximun and minimum) to quantify shape and which can be useful to identify shrimps, estimate their sizes, and even find a relationship between morphometric measures with respect to biomass.

Original languageEnglish
Title of host publicationRecent Trends in Image Processing and Pattern Recognition - 5th International Conference, RTIP2R 2022, Revised Selected Papers
EditorsKC Santosh, Ayush Goyal, Djamila Aouada, Aaisha Makkar, Yao-Yi Chiang, Satish K Singh
PublisherSpringer Science and Business Media Deutschland GmbH
Pages205-219
Number of pages15
ISBN (Print)9783031235986
DOIs
StatePublished - 2023
Event5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022 - Kingsville, United States
Duration: 1 Dec 20222 Dec 2022

Publication series

NameCommunications in Computer and Information Science
Volume1704 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022
Country/TerritoryUnited States
CityKingsville
Period1/12/222/12/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Chord length function
  • Shape analysis
  • Shrimp biomass estimation
  • Shrimp count

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