RANCANG BANGUN APLIKASI PENCARIAN SLOT PARKIR KOSONG UNTUK KENDARAAN RODA EMPAT DENGAN PENDEKATAN COMPUTER VISION

Main Article Content

Agma Tinoe Mauludy Duman Care Khrisne Komang Oka Saputra

Abstract

Parking space is a facility that must be available in public places, both in shopping areas, offices, hospitals and other places. In general, parking lots only provide parking slots to occupy cars without a system that provides information to the driver about the availability of parking slots, often the driver must surround the parking area to determine whether there are still parking slots that can be occupied. Design and build this application using the Computer Vision method, with the help of CCTV cameras. In making this application, the reference object for detection is a four-wheeled vehicle and the detection uses the Structural Similarity Index Measurement (SSIM) method by taking photos of full parking slots and empty parking slots with four-wheeled vehicles. Then two sample photos will be compared with the threshold method. After getting information about the availability of parking slots, the data will be sent to the server which will then be forwarded by the android application in real time. The results of designing this application have several things that are very influential on the level of detection, namely the intensity of light and camera position. Resistance to light changes of at least 50% of the template that has been made, while the distance of the camera to the parking slot is very influential. The farther the camera the smaller the precision produced by the system.

Downloads

Download data is not yet available.

Article Details

How to Cite
TINOE MAULUDY, Agma; CARE KHRISNE, Duman; OKA SAPUTRA, Komang. RANCANG BANGUN APLIKASI PENCARIAN SLOT PARKIR KOSONG UNTUK KENDARAAN RODA EMPAT DENGAN PENDEKATAN COMPUTER VISION. Jurnal SPEKTRUM, [S.l.], v. 7, n. 1, p. 36-40, mar. 2020. ISSN 2684-9186. Available at: <https://ojs.unud.ac.id/index.php/spektrum/article/view/58094>. Date accessed: 02 nov. 2024. doi: https://doi.org/10.24843/SPEKTRUM.2020.v07.i01.p5.
Section
Articles

Most read articles by the same author(s)

1 2 3 4 > >>