Automate Detection and Weight Estimation of Fish in Underwater 3D Images

Being able to determine the weight of fish is important information for fish breeding facilities. Current methods rely on manual measurements, but it is interesting to look into how underwater imaging can be used to automate these measurements. Underwater imaging is a complex problem due to light at...

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Bibliographic Details
Main Author: Nystad, Lars-Håkon Nohr
Other Authors: Elster, Anne Cathrine, Bø, Ketil, Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for datateknologi og informatikk
Format: Master Thesis
Language:English
Published: NTNU 2018
Subjects:
Online Access:http://hdl.handle.net/11250/2615876
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2615876 2023-05-15T15:32:47+02:00 Automate Detection and Weight Estimation of Fish in Underwater 3D Images Nystad, Lars-Håkon Nohr Elster, Anne Cathrine Bø, Ketil Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for datateknologi og informatikk 2018 http://hdl.handle.net/11250/2615876 eng eng NTNU ntnudaim:18122 http://hdl.handle.net/11250/2615876 54 Datateknologi (2 årig) Algoritmer og HPC Master thesis 2018 ftntnutrondheimi 2019-09-17T06:55:40Z Being able to determine the weight of fish is important information for fish breeding facilities. Current methods rely on manual measurements, but it is interesting to look into how underwater imaging can be used to automate these measurements. Underwater imaging is a complex problem due to light attenuation and poor water quality yielding lots of light scattering from an illuminating light source. In collaboration with Trollhetta and with the use of data from a cutting edge range-gated camera, we will tackle the problem of automating the measurement of the weight and size of atlantic salmon (Salmo salar) swimming freely inside a fish tank. The camera is manufactured by SINTEF Digital in collaboration with Odos Imaging and Bright Solutions, and illuminates the scene by the use of green light with a wavelength of 532nm. An Active Shape Model implementation is used as a backend to handle the problem of segmenting salmon in the given images. The segmentation algorithm detects the contour of the fish, and makes it easy to find both the length and height of the fish in image space. The segmented image is matched against the corresponding depth component of the image and the mean of all pixels is used as a measurement for the distance from the camera to the fish. By using the principal of similar triangles in the pinhole camera model we project information like length and height from image space into world space. The method proposed in this thesis can be regarded as a proof of concept, and a baseline for further research into this particular problem. Master Thesis Atlantic salmon Salmo salar NTNU Open Archive (Norwegian University of Science and Technology) Handle The ENVELOPE(161.983,161.983,-78.000,-78.000)
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
topic Datateknologi (2 årig)
Algoritmer og HPC
spellingShingle Datateknologi (2 årig)
Algoritmer og HPC
Nystad, Lars-Håkon Nohr
Automate Detection and Weight Estimation of Fish in Underwater 3D Images
topic_facet Datateknologi (2 årig)
Algoritmer og HPC
description Being able to determine the weight of fish is important information for fish breeding facilities. Current methods rely on manual measurements, but it is interesting to look into how underwater imaging can be used to automate these measurements. Underwater imaging is a complex problem due to light attenuation and poor water quality yielding lots of light scattering from an illuminating light source. In collaboration with Trollhetta and with the use of data from a cutting edge range-gated camera, we will tackle the problem of automating the measurement of the weight and size of atlantic salmon (Salmo salar) swimming freely inside a fish tank. The camera is manufactured by SINTEF Digital in collaboration with Odos Imaging and Bright Solutions, and illuminates the scene by the use of green light with a wavelength of 532nm. An Active Shape Model implementation is used as a backend to handle the problem of segmenting salmon in the given images. The segmentation algorithm detects the contour of the fish, and makes it easy to find both the length and height of the fish in image space. The segmented image is matched against the corresponding depth component of the image and the mean of all pixels is used as a measurement for the distance from the camera to the fish. By using the principal of similar triangles in the pinhole camera model we project information like length and height from image space into world space. The method proposed in this thesis can be regarded as a proof of concept, and a baseline for further research into this particular problem.
author2 Elster, Anne Cathrine
Bø, Ketil
Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for datateknologi og informatikk
format Master Thesis
author Nystad, Lars-Håkon Nohr
author_facet Nystad, Lars-Håkon Nohr
author_sort Nystad, Lars-Håkon Nohr
title Automate Detection and Weight Estimation of Fish in Underwater 3D Images
title_short Automate Detection and Weight Estimation of Fish in Underwater 3D Images
title_full Automate Detection and Weight Estimation of Fish in Underwater 3D Images
title_fullStr Automate Detection and Weight Estimation of Fish in Underwater 3D Images
title_full_unstemmed Automate Detection and Weight Estimation of Fish in Underwater 3D Images
title_sort automate detection and weight estimation of fish in underwater 3d images
publisher NTNU
publishDate 2018
url http://hdl.handle.net/11250/2615876
long_lat ENVELOPE(161.983,161.983,-78.000,-78.000)
geographic Handle The
geographic_facet Handle The
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source 54
op_relation ntnudaim:18122
http://hdl.handle.net/11250/2615876
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