Automated measurement of species and length of fish by computer vision

D. J. White; C. Svellingen; N. J.C. Strachan

doi:10.1016/j.fishres.2006.04.009

Automated measurement of species and length of fish by computer vision

D. J. White^*, C. Svellingen, N. J.C. Strachan

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

155 Citations (Scopus)

Abstract

Trials of a computer vision machine (The CatchMeter) for identifying and measuring different species of fish are described. The fish are transported along a conveyor underneath a digital camera. Image processing algorithms: determine the orientation of the fish utilising a moment-invariant method, identify whether the fish is a flatfish or roundfish with 100% accuracy, measure the length with a standard deviation of 1.2 mm and species with up to 99.8% sorting reliability for seven species of fish. The potential application of the system onboard both research and commercial ships is described. The machine can theoretically process up to 30,000 fish/h using a single conveyor based system.

Original language	English
Pages (from-to)	203-210
Number of pages	8
Journal	Fisheries Research
Volume	80
Issue number	2-3
DOIs	https://doi.org/10.1016/j.fishres.2006.04.009
Publication status	Published - Sep 2006

Keywords

Computer vision
Fish
Fish species
Image processing
Sorting

Access to Document

10.1016/j.fishres.2006.04.009Licence: Unspecified

Cite this

@article{62dfc675f985482691b872b52cd0611f,

title = "Automated measurement of species and length of fish by computer vision",

abstract = "Trials of a computer vision machine (The CatchMeter) for identifying and measuring different species of fish are described. The fish are transported along a conveyor underneath a digital camera. Image processing algorithms: determine the orientation of the fish utilising a moment-invariant method, identify whether the fish is a flatfish or roundfish with 100% accuracy, measure the length with a standard deviation of 1.2 mm and species with up to 99.8% sorting reliability for seven species of fish. The potential application of the system onboard both research and commercial ships is described. The machine can theoretically process up to 30,000 fish/h using a single conveyor based system.",

keywords = "Computer vision, Fish, Fish species, Image processing, Sorting",

author = "White, {D. J.} and C. Svellingen and Strachan, {N. J.C.}",

note = "The Authors would like to thank Jan-Tore {\O}vredal and Bj{\o}rn Totland of the Institute of Marine Research in Bergen for their help and comments regarding this work and also for arranging the test cruises on the Norwegian G. O. Sars research vessel. Erik Andersen of Matcon in Denmark for his advice regarding the mechanical systems of the CatchMeter. The companies and institutions that funded this work: The Norwegian Research Council, The Norwegian Fishery Research Fund, The Nordic Council of Ministers, The Institute of Marine Research in Bergen and Scantrol. ",

year = "2006",

month = sep,

doi = "10.1016/j.fishres.2006.04.009",

language = "English",

volume = "80",

pages = "203--210",

journal = "Fisheries Research",

issn = "0165-7836",

publisher = "Elsevier Science B. V.",

number = "2-3",

}

TY - JOUR

T1 - Automated measurement of species and length of fish by computer vision

AU - White, D. J.

AU - Svellingen, C.

AU - Strachan, N. J.C.

N1 - The Authors would like to thank Jan-Tore Øvredal and Bjørn Totland of the Institute of Marine Research in Bergen for their help and comments regarding this work and also for arranging the test cruises on the Norwegian G. O. Sars research vessel. Erik Andersen of Matcon in Denmark for his advice regarding the mechanical systems of the CatchMeter. The companies and institutions that funded this work: The Norwegian Research Council, The Norwegian Fishery Research Fund, The Nordic Council of Ministers, The Institute of Marine Research in Bergen and Scantrol.

PY - 2006/9

Y1 - 2006/9

N2 - Trials of a computer vision machine (The CatchMeter) for identifying and measuring different species of fish are described. The fish are transported along a conveyor underneath a digital camera. Image processing algorithms: determine the orientation of the fish utilising a moment-invariant method, identify whether the fish is a flatfish or roundfish with 100% accuracy, measure the length with a standard deviation of 1.2 mm and species with up to 99.8% sorting reliability for seven species of fish. The potential application of the system onboard both research and commercial ships is described. The machine can theoretically process up to 30,000 fish/h using a single conveyor based system.

AB - Trials of a computer vision machine (The CatchMeter) for identifying and measuring different species of fish are described. The fish are transported along a conveyor underneath a digital camera. Image processing algorithms: determine the orientation of the fish utilising a moment-invariant method, identify whether the fish is a flatfish or roundfish with 100% accuracy, measure the length with a standard deviation of 1.2 mm and species with up to 99.8% sorting reliability for seven species of fish. The potential application of the system onboard both research and commercial ships is described. The machine can theoretically process up to 30,000 fish/h using a single conveyor based system.

KW - Computer vision

KW - Fish

KW - Fish species

KW - Image processing

KW - Sorting

UR - http://www.scopus.com/inward/record.url?scp=33751117744&partnerID=8YFLogxK

U2 - 10.1016/j.fishres.2006.04.009

DO - 10.1016/j.fishres.2006.04.009

M3 - Article

AN - SCOPUS:33751117744

VL - 80

SP - 203

EP - 210

JO - Fisheries Research

JF - Fisheries Research

SN - 0165-7836

IS - 2-3

ER -

Automated measurement of species and length of fish by computer vision

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this