Performance Evaluation of YOLO-Based Deep Learning Models for Real-Time Armour Unit Detection with Image Pre-processing Method

Firmansyah Putra Pratama*, Alfan Rizaldy Pratama, Dewi Mutiara Sari, Bayu Sandi Marta, R. Haryo Dwito Armono

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Breakwater construction in Indonesia still relies on divers to direct the placement of rock armour units, which is risky and time-constrained. This research aims to replace the diver's task with a deep learning-based vision system using YOLO-based deep learning models. The system utilizes image pre-processing technology by applying histogram equalization (HE) techniques to improve image quality before the detection process. This research evaluates the performance of the YOLO-based deep learning models in detecting armour units in real-time with a focus on various environmental conditions, which are clear and murky water. The analysis reveals clear water consistently supports higher average frame rates (FPS) compared to murky water, maintaining efficient frame processing across all models. In murky water, histogram equalization significantly enhances detection accuracy from 60% to 80% for YOLOv4-tiny and YOLOv7-tiny, demonstrating its effectiveness in challenging conditions. Notably, accuracy remains at 100% for all models in clear water, underscoring their robust performance under optimal visibility conditions.

Original languageEnglish
Title of host publication2024 International Electronics Symposium
Subtitle of host publicationShaping the Future: Society 5.0 and Beyond, IES 2024 - Proceeding
EditorsAndhik Ampuh Yunanto, Afifah Dwi Ramadhani, Yanuar Risah Prayogi, Putu Agus Mahadi Putra, Weny Mistarika Rahmawati, Muhammad Rizani Rusli, Fitrah Maharani Humaira, Faridatun Nadziroh, Nihayatus Sa'adah, Nailul Muna, Aris Bahari Rizki
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages541-546
Number of pages6
ISBN (Electronic)9798350391992
DOIs
Publication statusPublished - 2024
Event26th International Electronics Symposium, IES 2024 - Denpasar, Indonesia
Duration: 6 Aug 20248 Aug 2024

Publication series

Name2024 International Electronics Symposium: Shaping the Future: Society 5.0 and Beyond, IES 2024 - Proceeding

Conference

Conference26th International Electronics Symposium, IES 2024
Country/TerritoryIndonesia
CityDenpasar
Period6/08/248/08/24

Keywords

  • armour units
  • breakwater
  • deep learning
  • image pre-processing
  • real-time detection

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