A Machine Vision Approach for Recognizing Coastal Fish
Objetos digitales
| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20220034746 | ||
| 003 | MAP | ||
| 005 | 20221124095200.0 | ||
| 008 | 221124e20221205esp|||p |0|||b|eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a922.134 | ||
| 245 | 1 | 2 | $aA Machine Vision Approach for Recognizing Coastal Fish$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 | |
| 773 | 0 | $wMAP20200034445$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 |