Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)

Design of Biofouling Level Classification System Using Haar-Cascade Classifier And Local Binary Pattern Histogram

Authors
Yuning Widiarti1, *, Fasa Imana Faumi2
1Marine Electrical Engineering Shipbuilding Institute of Polytechnic Surabaya, Surabaya, Indonesia
2Automation Engineering Shipbuilding Institute of Polytechnic Surabaya, Surabaya, Indonesia
*Corresponding author. Email: yuning.widiarti@ppns.ac.id
Corresponding Author
Yuning Widiarti
Available Online 17 February 2024.
DOI
10.2991/978-94-6463-364-1_73How to use a DOI?
Keywords
Biofoulin; Jetson Nano; ROV; Haar Cascade; Local Binary Pattern; Classification
Abstract

The shipbuilding industry still faces challenges and problems. One of them is biofouling on ships, a major problem that can lead to increased fuel consumption and a higher risk of spreading invasive species. The shipbuilding industry is a strategic and competitive domestic industry that deserves to be developed. Biofouling consists of five levels ranging from 0–100% fouling on the ship’s hull. Therefore, the countermeasures carried out so that the process of fouling the ship’s hull by biofouling is not too severe is the creation of a system to identify fouling on the ship’s hull. Based on these problems, in this study, the researchers classified the level of biofouling on the hull using the Haar Cascade Classifier method and the Local Binary Pattern Histogram where the system input was in the form of biofouling images and the system output was in the form of levels of biofouling images that were inspected. This design is applied to the ROV which is equipped with a servo motor on the camera so that it can move in the direction of the yaw axis and pitch axis which can be controlled using a joystick. In this study, it was found that the accuracy of success using the Haar Cascade Classifier reached 90% while using the Local Binary Pattern Histogram obtained an accuracy of 86%. The accuracy of the Haar Cascade Classifier and LBPH methods which have been integrated with the GUI (Graphical User Interface) shows that each level has a different number of pixels.

Copyright
© 2024 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 International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
Series
Advances in Engineering Research
Publication Date
17 February 2024
ISBN
10.2991/978-94-6463-364-1_73
ISSN
2352-5401
DOI
10.2991/978-94-6463-364-1_73How to use a DOI?
Copyright
© 2024 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

TY  - CONF
AU  - Yuning Widiarti
AU  - Fasa Imana Faumi
PY  - 2024
DA  - 2024/02/17
TI  - Design of Biofouling Level Classification System Using Haar-Cascade Classifier And Local Binary Pattern Histogram
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
PB  - Atlantis Press
SP  - 801
EP  - 814
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-364-1_73
DO  - 10.2991/978-94-6463-364-1_73
ID  - Widiarti2024
ER  -