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Keywords = tuna shoal searching

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12 pages, 4497 KB  
Article
Application of Feature Point Matching Technology to Identify Images of Free-Swimming Tuna Schools in a Purse Seine Fishery
by Qinglian Hou, Cheng Zhou, Rong Wan, Junbo Zhang and Feng Xue
J. Mar. Sci. Eng. 2021, 9(12), 1357; https://doi.org/10.3390/jmse9121357 - 1 Dec 2021
Cited by 3 | Viewed by 2554
Abstract
Tuna fish school detection provides information on the fishing decisions of purse seine fleets. Here, we present a recognition system that included fish shoal image acquisition, point extraction, point matching, and data storage. Points are a crucial characteristic for images of free-swimming tuna [...] Read more.
Tuna fish school detection provides information on the fishing decisions of purse seine fleets. Here, we present a recognition system that included fish shoal image acquisition, point extraction, point matching, and data storage. Points are a crucial characteristic for images of free-swimming tuna schools, and point algorithm analysis and point matching were studied for their applications in fish shoal recognition. The feature points were obtained by using one of the best point algorithms (scale invariant feature transform, speeded up robust features, oriented fast and rotated brief). The k-nearest neighbors (KNN) algorithm uses ‘feature similarity’ to predict the values of new points, which means that new data points will be assigned a value based on how closely they match the points that exist in the database. Finally, we tested the model, and the experimental results show that the proposed method can accurately and effectively recognize tuna free-swimming schools. Full article
(This article belongs to the Special Issue Artificial Intelligence in Marine Science and Engineering)
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