DETEKSI JUMLAH SLOT PARKIR KOSONG MENGGUNAKAN METODE BINARY THRESHOLD

Azis, Reno Abdul (2025) DETEKSI JUMLAH SLOT PARKIR KOSONG MENGGUNAKAN METODE BINARY THRESHOLD. Sarjana (S1) thesis, Universitas Islam 45.

	Text PENDAHULUAN.pdf Download (367kB)
	Text BAB I.pdf Restricted to Repository staff only Download (87kB) | Request a copy
	Text BAB II.pdf Restricted to Repository staff only Download (123kB) | Request a copy
	Text BAB III.pdf Restricted to Repository staff only Download (46kB) | Request a copy
	Text BAB IV.pdf Restricted to Repository staff only Download (172kB) | Request a copy
	Text BAB V.pdf Restricted to Repository staff only Download (31kB) | Request a copy
	Text DAFTAR PUSTAKA.pdf Download (144kB)

Abstract

The issue of limited parking space in public areas continues to grow alongside the increasing number of vehicles, creating a need for a system capable of automatically and efficiently detecting available parking slots. This study aims to compare two line detection methods in parking areas, namely the Hough Transform and Binary Threshold, and to determine the most effective method for identifying the number of available slots using a Computer Vision approach. The data used consists of non-real-time simulated images of parking areas, processed using Python and the OpenCV library. The results show that the Binary Threshold method outperforms the Hough Transform in accurately detecting parking slot lines, particularly in areas with continuous lines and horizontal layouts. Testing on 10 sample images indicates that the system can detect the number of available slots with 100% accuracy. These findings demonstrate that the Binary Threshold method is effective for implementing an automated parking slot detection system based on image processing.

Actions (login required)

View Item