A Machine Vision Approach for Recognizing Coastal Fish

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<title>Machine Vision Approach for Recognizing Coastal Fish</title>
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<abstract displayLabel="Summary">Coastal 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%.

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<accessCondition type="use and reproduction">La copia digital se distribuye bajo licencia "Attribution 4.0 International (CC BY NC 4.0)"</accessCondition>
<note type="statement of responsibility">Afiq Raihan...[et.al.]</note>
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<topic>Inteligencia artificial</topic>
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<title>Revista Iberoamericana de Inteligencia Artificial</title>
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<publisher> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</publisher>
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<identifier type="issn">1988-3064</identifier>
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<text>05/12/2022 Volumen 25 Número 70 - diciembre 2022 , p. 13-32</text>
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