Extreme Learning Machine for Parking Slot Recognition in Smart Parking System
In the modern era, technology has become an integral part of human life, particularly in image processing. This advanced technology is now applied to parking areas to identify vacant parking spaces. The application is designed to detect empty parking slots in real time using image data captured by a camera as input. The system then automatically scans for available parking spaces, displaying the results on the interface with green indicators for empty slots and red for occupied ones. The process involves several key stages, such as image pre-processing, image segmentation, and object detection. The system employs the Extreme Learning Machine (ELM) method to enhance its object detection capabilities. This system achieves a high accuracy rate of 94%under well-lit conditions. This novel technology optimizes parking management, providing an effective and dependable method to monitor parking availability in real time.
Authors
- Romi Fadillah Rahmat (ORCID: https://orcid.org/0000-0003-4855-294X)
- Mohd Amiruddin Abd Rahman (ORCID: https://orcid.org/0000-0003-0951-9450)
- Sharfina Faza (ORCID: https://orcid.org/0000-0001-6856-5380)
- Pauzi Ibrahim Nainggolan
- Riza Sulaiman
- Irwanda Syahputra
Institutions
- Universiti Putra Malaysia (MY)
- State University of Medan (ID)
- Universitas Sumatera Utara (ID)
- National University of Malaysia (MY)
Publication Details
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1109/elticom64085.2024.10865423
- Primary Topic
- Smart Parking Systems Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00