Rafli Pratama, Muhammad (2025) OPTIMASI DETEKSI PELANGGARAN PENGGUNAAN HELM PADA TRAFFIC LIGHT BERBASIS YOLO V7 DENGAN CLAHE ENHANCEMENT UNTUK KONDISI LOW-LIGHT. Undergraduate thesis, UPN Veteran Jawa Timur.
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text
Cover.pdf Restricted to Repository staff only Download (608kB) | Request a copy |
|
Text
Bab1.pdf Restricted to Repository staff only Download (88kB) | Request a copy |
|
Text
Bab 2.pdf Restricted to Repository staff only until 21 May 2027. Download (370kB) | Request a copy |
|
Text
Bab 3.pdf Restricted to Repository staff only until 21 May 2027. Download (834kB) | Request a copy |
|
Text
Bab 4.pdf Restricted to Repository staff only until 21 May 2027. Download (1MB) | Request a copy |
|
Text
Bab 5.pdf Download (9kB) |
|
Text
Daftar Pustaka.pdf Download (82kB) |
Abstract
Traffic safety, especially regarding the use of helmets by motorcyclists, is still a crucial issue in Indonesia. This research aims to develop a system to detect helmet use violations in traffic light areas, especially in low-light conditions. The method used is the integration of You Only Look Once version 7 (YOLOv7) algorithm with Contrast Limited Adaptive Histogram Equalization (CLAHE) image enhancement technique. The dataset used comes from traffic IP camera videos in Surabaya and public datasets that have gone through pre-processing, annotation, augmentation, and model training stages. Tests were conducted by comparing the YOLOv7 model without CLAHE and with CLAHE in low-light conditions. The test results show that the model with CLAHE obtained a mean average precision (mAP) of 90.15%, precision of 87.4%, recall of 88.4%, and F1-score of 92%, which is superior to the model without CLAHE. This finding shows that CLAHE is effective in improving object detection performance under low-light conditions. The developed system is expected to support automatic enforcement of traffic rules and contribute to improving driving safety.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||||||
| Subjects: | T Technology > T Technology (General) > T385 Computer Graphics | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Muhammad Rafli Pratama | ||||||||||||
| Date Deposited: | 26 May 2025 04:14 | ||||||||||||
| Last Modified: | 28 Oct 2025 06:37 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/36412 |
Actions (login required)
 |
View Item |