Detection and counting of uneaten food pellets in a sea cage using image analysis

Foster, M.; Petrell, Royann J.; Ito, M.R.; Ward, Rabab K.

doi:10.1016/0144-8609(94)00006-m

Cited by 61 publications

(25 citation statements)

References 7 publications

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“…This is why the detection of jellyfish has not been done successfully in comparison with the other research subjects by image analysis (ex. Foster et al, 1995;Tillett et al, 1999;Fresno et al, 2005). The underwater observation of jellyfish by CCD camera is one of important techniques for the development of automatic detection and removal system of jellyfish.…”

Section: Introductionmentioning

confidence: 99%

Detection and removal of jellyfish using underwater image analysis

Matsuura

Fujisawa

Ishikawa³

2007

J Vis

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Section: Introductionmentioning

confidence: 99%

Detection and removal of jellyfish using underwater image analysis

Matsuura

Fujisawa

Ishikawa³

2007

J Vis

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“…Such a system will improve the control of the pellet size and secure uniformity of pellets. Foster et al (1995) and Parsonage (2001) have both shown that it is possible to measure fish feed pellet size by image analysis. However, their work is only valid for measurements on single pellets, which limits the usability in relation to industrial production where the production process never leads to singlewise pellets.…”

Section: Control Of Extruded Food and Feed Productsmentioning

confidence: 99%

Spectral Imaging as a Tool in Food Research and Quality Monitoring of Food Production

Frosch

Dissing

Adler‐Nissen

et al. 2011

Wide Spectra of Quality Control

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“…1 The original image Image processing Due to the influence of the environment, the images are mixed with the noise signal, which influents the accuracy of image recognition. First of all, image filtering process should be done to reduce the interference of the noise signal; then study the feature of feeding images through the image enhancement and feature extraction [7].…”

Section: Research On the Regularities Of Fish Feedingmentioning

confidence: 99%

Research on Smart Cast for Fish Cage Aquaculture based on image processing

Hu¹,

Zheng²,

Qiao³

et al. 2016

Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

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Abstract. In recent years, with the development of fish cage aquaculture technology, the traditional way of bait casting cannot meet the growing demands any more. As fishes feed with certain regularities, it is important to acquire the feeding conditions of the fishes. Through analyzing the images of fishes feed by the way of image processing, the feature of the shape and the area of fishes is extracted. The gross of feeding is setup based on the shape, which reflects the weight of fish. The feeding amount is changed with the variation of the image of fish in feeding at real time. The cast program according the extracted feature and the cage aquaculture experiment is designed to verify the feeding effect. Experimental result shows that the smart cast can setup the bait according to the growing requirement of the fishes. The bait utilization will be increased, and water pollution will be reduced, and the fish quality can be improved as well through the smart cast system.

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Detection and counting of uneaten food pellets in a sea cage using image analysis

Cited by 61 publications

References 7 publications

Detection and removal of jellyfish using underwater image analysis

Detection and removal of jellyfish using underwater image analysis

Spectral Imaging as a Tool in Food Research and Quality Monitoring of Food Production

Research on Smart Cast for Fish Cage Aquaculture based on image processing

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