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  • 标题:A Machine Vision Approach for Recognizing Coastal Fish
  • 本地全文:下载
  • 作者:Afiq Raihan ; Israt Sharmin ; B M Marjan Khan
  • 期刊名称:Inteligencia Artificial : Ibero-American Journal of Artificial Intelligence
  • 印刷版ISSN:1137-3601
  • 电子版ISSN:1988-3064
  • 出版年度:2022
  • 卷号:25
  • 期号:70
  • 语种:English
  • 出版社:Spanish Association for Intelligence Artificial
  • 摘要: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%.
  • 关键词:Fish species recognition;Machine vision;Feature extraction;Principal component analysis;k-nearest neighbor;Performance metric.
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