Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)

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Classification of Nile Tilapia’s Freshness Based on Eyes and Gills Using Support Vector Machine

Authors
Muhammad Imam Syarwani1, Gibran Satya Nugraha1, *, Ramaditia Dwiyansaputra1, Khairunnas2
1Informatics Engineering Department, University of Mataram, Mataram, Indonesia
2Computer Engineering Department, Vistula University, Warszawa, Poland
*Corresponding author. Email: gibransn@unram.ac.id
Corresponding Author
Gibran Satya Nugraha
Available Online 26 December 2022.
DOI
10.2991/978-94-6463-084-8_15How to use a DOI?
Keywords
Nile Tilapia; Classification; Feature; Image Processing; Fish
Abstract

Fish is one of the foodstuffs that contain high protein and essential amino acids the body needs. Nile Tilapia is a fish that the people of Indonesia widely consume. The high nutritional content of tilapia and affordable prices make this fish popular with the public. The difference between fresh and unfresh tilapia can be assessed from organoleptic tests, including gill color, texture, and smell. Consumers can check by looking at the condition of tilapia based on its distinguishing physical characteristics such as eyes, gills, flesh texture, skin, and fish mucus. However, not everyone knows and understands these typical characteristics. Therefore, we need a system that can classify the freshness level of tilapia. In this study, the freshness level of tilapia will be classified based on the color and texture features of the eyes and gills using the Support Vector Machine. The GLCM approach is used to extract texture features, whereas the HSV method is utilized to extract color features. The total number of photos used in this investigation was 840, which were separated into training and testing data. With an image size of 256 × 256 pixels, the combined feature of HSV + GLCM achieves the highest accuracy of 94.28%.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
Series
Advances in Computer Science Research
Publication Date
26 December 2022
ISBN
978-94-6463-084-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-084-8_15How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Imam Syarwani
AU  - Gibran Satya Nugraha
AU  - Ramaditia Dwiyansaputra
AU  - Khairunnas
PY  - 2022
DA  - 2022/12/26
TI  - Classification of Nile Tilapia’s Freshness Based on Eyes and Gills Using Support Vector Machine
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 156
EP  - 168
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_15
DO  - 10.2991/978-94-6463-084-8_15
ID  - Syarwani2022
ER  -