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FishDeTec: a fish identification application using image recognition approach

The underwater imagery processing is always in high demand, especially the fish species identification. This activity is as important not only for the biologist, scientist, and fisherman, but it is also important for the education purpose. It has been reported that there are more than 200 species of...

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Main Authors: Mohd Rum, Siti Nurulain, Nawawi, Fariz Az Zuhri
Format: Article
Language:English
Published: Science and Information Organization 2021
Online Access:http://psasir.upm.edu.my/id/eprint/97350/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/97350/
https://thesai.org/Publications/ViewPaper?Volume=12&Issue=3&Code=IJACSA&SerialNo=12
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spelling my.upm.eprints.973502022-08-26T08:56:10Z http://psasir.upm.edu.my/id/eprint/97350/ FishDeTec: a fish identification application using image recognition approach Mohd Rum, Siti Nurulain Nawawi, Fariz Az Zuhri The underwater imagery processing is always in high demand, especially the fish species identification. This activity is as important not only for the biologist, scientist, and fisherman, but it is also important for the education purpose. It has been reported that there are more than 200 species of freshwater fish in Malaysia. Many attempts have been made to develop the fish recognition and classification via image processing approach, however, most of the existing work are developed for the saltwater fish species identification and used for a specific group of users. This research work focuses on the development of a prototype system named FishDeTec to the detect the freshwater fish species found in Malaysia through the image processing approach. In this study, the proposed predictive model of the FishDeTec is developed using the VGG16, is a deep Convolutional Neural Network (CNN) model for a large-scale image classification processing. The experimental study indicates that our proposed model is a promising result. Science and Information Organization 2021 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/97350/1/ABSTRACT.pdf Mohd Rum, Siti Nurulain and Nawawi, Fariz Az Zuhri (2021) FishDeTec: a fish identification application using image recognition approach. International Journal of Advanced Computer Science and Applications, 12 (3). 102 - 106. ISSN 2158-107X; ESSN: 2156-5570 https://thesai.org/Publications/ViewPaper?Volume=12&Issue=3&Code=IJACSA&SerialNo=12 10.14569/IJACSA.2021.0120312
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The underwater imagery processing is always in high demand, especially the fish species identification. This activity is as important not only for the biologist, scientist, and fisherman, but it is also important for the education purpose. It has been reported that there are more than 200 species of freshwater fish in Malaysia. Many attempts have been made to develop the fish recognition and classification via image processing approach, however, most of the existing work are developed for the saltwater fish species identification and used for a specific group of users. This research work focuses on the development of a prototype system named FishDeTec to the detect the freshwater fish species found in Malaysia through the image processing approach. In this study, the proposed predictive model of the FishDeTec is developed using the VGG16, is a deep Convolutional Neural Network (CNN) model for a large-scale image classification processing. The experimental study indicates that our proposed model is a promising result.
format Article
author Mohd Rum, Siti Nurulain
Nawawi, Fariz Az Zuhri
spellingShingle Mohd Rum, Siti Nurulain
Nawawi, Fariz Az Zuhri
FishDeTec: a fish identification application using image recognition approach
author_facet Mohd Rum, Siti Nurulain
Nawawi, Fariz Az Zuhri
author_sort Mohd Rum, Siti Nurulain
title FishDeTec: a fish identification application using image recognition approach
title_short FishDeTec: a fish identification application using image recognition approach
title_full FishDeTec: a fish identification application using image recognition approach
title_fullStr FishDeTec: a fish identification application using image recognition approach
title_full_unstemmed FishDeTec: a fish identification application using image recognition approach
title_sort fishdetec: a fish identification application using image recognition approach
publisher Science and Information Organization
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/97350/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/97350/
https://thesai.org/Publications/ViewPaper?Volume=12&Issue=3&Code=IJACSA&SerialNo=12
_version_ 1743108548163796992
score 13.211869

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