Abstract:
t 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,
the 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 sixteen features comprising four
classes is extracted to be fed to a classifier. For reducing the number of features, PCA is applied. To recognize
coastal fish, five classical machine learning classifiers are performed, where k-NN provides a potential accuracy of
up to 98.89%.
