Imaging sonar tracking of salmon for size and tail beat frequency

Kupilik, Matthew; Petersen, Todd

doi:10.1109/globalsip.2014.7032297

Cited by 3 publications

(9 citation statements)

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“…Similar to the tailbeat measurement approach in Kupilik and Petersen (2014), the method applied herein utilized metrics of measurements extracted from each frame rather than applying the maximum‐intensity echogram. To combine all frames where a fish was visible during its passage through the sonar field, a fish tracking feature was used in Echoview.…”

Section: Methodsmentioning

confidence: 99%

“…Observing swimming behaviour of fish from imaging sonar footage has frequently been presented as a speciesidentification tool (Mueller et al 2008(Mueller et al , 2010Kupilik and Petersen 2014;Kirk et al 2015;Bothmann et al 2016). Tailbeat frequency measurements have been successfully used for distinguishing between Chinook Salmon Oncorhynchus tshawytscha and Sockeye Salmon O. nerka using an echogram that presents the maximum intensity value for each pixel (Mueller et al 2010).…”

mentioning

confidence: 99%

“…Automatic sonar data processing methods are increasingly used for rapidly processing imaging sonar data (Boswell et al 2008;Handegard and Williams 2008;Han et al 2009;Kang 2011;Petreman et al 2014;Yin et al 2020;Helminen and Linnansaari 2021). Automation is typically used to count the fish from the footage, but other information such as fish size (Han et al 2009;Helminen et al 2020) or the tailbeat frequency (Kupilik and Petersen 2014) can also be generated. Instead of using the maximum-intensity echograms, the tailbeats can also be calculated automatically by observing changes in body concavity throughout the fish passage in the sonar beam (Kupilik and Petersen 2014).…”

mentioning

confidence: 99%

“…Automation is typically used to count the fish from the footage, but other information such as fish size (Han et al 2009;Helminen et al 2020) or the tailbeat frequency (Kupilik and Petersen 2014) can also be generated. Instead of using the maximum-intensity echograms, the tailbeats can also be calculated automatically by observing changes in body concavity throughout the fish passage in the sonar beam (Kupilik and Petersen 2014).…”

mentioning

confidence: 99%

“…Observing swimming behaviour of fish from imaging sonar footage has frequently been presented as a species‐identification tool (Mueller et al. 2008, 2010; Kupilik and Petersen 2014; Kirk et al. 2015; Bothmann et al.…”

mentioning

confidence: 99%

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Measuring Tailbeat Frequencies of Three Fish Species from Adaptive Resolution Imaging Sonar Data

2021

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Imaging sonars, such as the Adaptive Resolution Imaging Sonar (ARIS), provide high-resolution sonar data that are used in fisheries research and management. While sonar methods have enormous potential for making population estimates, species identification via sonar remains an unresolved challenge. One method that may overcome this challenge involves measuring tailbeat frequencies to guide species differentiation. The tailbeat frequencies of three commonly sympatric anadromous fish species of eastern North America, Atlantic Salmon Salmo salar, Striped Bass Morone saxatilis, and American Shad Alosa sapidissima, were measured from imaging sonar data collected in an experimental low-flow, short-range setup. The frequencies were significantly different between the species (mean ± 1 SD beats/s: 0.6 ± 0.3 [Atlantic Salmon], 0.9 ± 0.2 [Striped Bass], and 1.4 ± 0.3 [American Shad]) when measured using a previously established manual method. Building on this, an automated method was developed and tested, and the method showed promising results. However, when compared to manually identified number of beats the error was large (on average, 1.1 [Atlantic Salmon], 4.8 [Striped Bass], and −0.4 [American Shad] beats in a fish track), especially in high fish densities. Despite the limitations, the automated method has utility in fisheries management when high-quality data can be collected for species with differing tailbeat frequencies.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Measuring Tailbeat Frequencies of Three Fish Species from Adaptive Resolution Imaging Sonar Data

2021

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Detection and characterisation of deep-sea benthopelagic animals from an autonomous underwater vehicle with a multibeam echosounder: A proof of concept and description of data-processing methods

Dunlop

Jarvis²,

Benoit‐Bird

et al. 2018

Deep Sea Research Part I: Oceanographic Research Papers

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Monitoring fish using imaging sonar: Capacity, challenges and future perspective

Wei

Duan

2022

Fish and Fisheries

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The demand for fish products, which provide crucial protein for humans, is rising as the global population grows. In contrast, fish stock is declining due to human activity, environmental changes and overfishing. Fish monitoring provides valuable support data for effective fishery management and ecosystem conservation. The common monitoring methods are based on manual sampling, which is time-consuming, laborious and intrusive. Imaging sonar is a hydroacoustic system that produces acoustic images similar to optical images by transmitting and receiving sound waves, allowing for in situ monitoring of fish non-intrusively in the dark and turbid water environments where optical cameras are limited. In the last decade, imaging sonar, especially high frequency multibeam forward-looking sonar and side-scan sonar, has been widely used in fish monitoring. We reviewed the literature from the previous decade on the use of these two types of imaging sonar in fish species identification, abundance estimation, length measurement and behaviour analysis, as well as the sonar imagery processing concerning fish. The review results show that these imaging sonars are efficient and effective tools for fish monitoring in complex environments. The challenges include(1) the recognition of small fish forming dense aggregations; (2) species identification, which limits their use in species-specific studies; (3) time-consuming massive data processing. Therefore, advanced algorithms for sonar imagery processing and integrations with other sampling technologies are needed for future development.

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Imaging sonar tracking of salmon for size and tail beat frequency

Cited by 3 publications

References 12 publications

Measuring Tailbeat Frequencies of Three Fish Species from Adaptive Resolution Imaging Sonar Data

Measuring Tailbeat Frequencies of Three Fish Species from Adaptive Resolution Imaging Sonar Data

Detection and characterisation of deep-sea benthopelagic animals from an autonomous underwater vehicle with a multibeam echosounder: A proof of concept and description of data-processing methods

Monitoring fish using imaging sonar: Capacity, challenges and future perspective

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