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A Machine Vision Approach for Recognizing Coastal Fish

A Machine Vision Approach for Recognizing Coastal Fish
Recurso electrónico / Electronic resource
MARC record
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001  MAP20220034746
003  MAP
005  20221124095200.0
008  221124e20221205esp|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎922.134
24512‎$a‎A Machine Vision Approach for Recognizing Coastal Fish‎$c‎Afiq Raihan...[et.al.]
520  ‎$a‎Coastal fish is one of the prominent marine resources, which takes a necessary role in the economic growth of a country. Because of environmental issues along with other reasons, not only most of the marine resources are diminishing but also many coastal fishes are getting extinct gradually. As a result, the young peoples have insufficient knowledge of coastal fish. This issue can be solved with the use of vision-based technologies. To deal with this situation, a coastal fish recognition system based on machine vision is conceived, which can be approached by the images of coastal fish that are captured with a portable device and identify the fish to recognize fish. Numerous experimental analyses are executed to exhibit the benefit of this proposed expert system. In the beginning, conversion of a color image into a gray-scale image occurs and the gray-scale histogram is developed. Using the histogram-based method, image segmentation is conducted. After that, a set of thirteen features comprising of four classes is extracted to be fed to a classifier. For reducing the number of features, PCA is applied. To recognize coastal fish, three cutting-edge classifiers are performed, where k-NN provides a potential accuracy of up to 98.7%.
540  ‎$a‎La copia digital se distribuye bajo licencia "Attribution 4.0 International (CC BY NC 4.0)"‎$f‎‎$u‎https://creativecommons.org/licenses/by-nc/4.0‎$9‎64
650 4‎$0‎MAPA20080611200‎$a‎Inteligencia artificial
650 4‎$0‎MAPA20080539498‎$a‎Pesca
7730 ‎$w‎MAP20200034445‎$g‎05/12/2022 Volumen 25 Número 70 - diciembre 2022 , p. 13-32‎$x‎1988-3064‎$t‎Revista Iberoamericana de Inteligencia Artificial‎$d‎ : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-
856  ‎$q‎application/pdf‎$w‎1118277‎$y‎Recurso electrónico / Electronic resource