Street-Based Parking Lot Detection With Image Processing And Deep Learning

Due to the rapidly increasing number of vehicles and urbanization, the use of parking spaces on the streets has increased significantly. Many studies have been carried out on the determination of parking spaces by using the lines in the parking areas. However, the usage areas of this method are very limited since these lines are not found in every parking area. In this research, a unique study has been presented to determine the empty and occupied parking spaces in the parking area by processing the images from the cameras located at high points on the streets with depth calculation, perspective transformation and certain image processing techniques within the framework of specific features. Empty and full parking lots were determined by utilizing perspective transformation and depth measurement techniques, and the data obtained were transferred to the Real-Time Database environment. In addition to determining the parking spaces, the study also aims to inform users through the mobile application and to prevent traffic congestion, extra fuel consumption, waste of time and air pollution caused by fuel consumption.

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Eser Adı
(dc.title)
Street-Based Parking Lot Detection With Image Processing And Deep Learning
Yazar
(dc.contributor.author)
Ahmet Fatih Mustaçoğlu
Yayın Yılı
(dc.date.issued)
2024
Tür
(dc.type)
Makale
Özet
(dc.description.abstract)
Due to the rapidly increasing number of vehicles and urbanization, the use of parking spaces on the streets has increased significantly. Many studies have been carried out on the determination of parking spaces by using the lines in the parking areas. However, the usage areas of this method are very limited since these lines are not found in every parking area. In this research, a unique study has been presented to determine the empty and occupied parking spaces in the parking area by processing the images from the cameras located at high points on the streets with depth calculation, perspective transformation and certain image processing techniques within the framework of specific features. Empty and full parking lots were determined by utilizing perspective transformation and depth measurement techniques, and the data obtained were transferred to the Real-Time Database environment. In addition to determining the parking spaces, the study also aims to inform users through the mobile application and to prevent traffic congestion, extra fuel consumption, waste of time and air pollution caused by fuel consumption.
Açık Erişim Tarihi
(dc.date.available)
2024-06-30
Yayıncı
(dc.publisher)
Springer Science and Business Media Deutschland GmbH
Dil
(dc.language.iso)
En
Konu Başlıkları
(dc.subject)
Image processing
Konu Başlıkları
(dc.subject)
Deep learning
Konu Başlıkları
(dc.subject)
Vehicle detection
Konu Başlıkları
(dc.subject)
Smart parking systems
Konu Başlıkları
(dc.subject)
Depth analysis
Tek Biçim Adres
(dc.identifier.uri)
https://hdl.handle.net/20.500.14081/2105
ISSN
(dc.identifier.issn)
1863-1703
Dergi
(dc.relation.journal)
Signal, Image and Video Processing
Esere Katkı Sağlayan
(dc.contributor.other)
Mustacoglu, Ahmet Fatih
Esere Katkı Sağlayan
(dc.contributor.other)
Sayar, Ahmet
DOI
(dc.identifier.doi)
10.1007/s11760-024-03206-0
Orcid
(dc.identifier.orcid)
0000-0002-5236-3917
wosquality
(dc.identifier.wosquality)
Q3
wosauthorid
(dc.contributor.wosauthorid)
AAA-2829-2021
Department
(dc.contributor.department)
Bilgisayar Mühendisliği (İngilizce)
Wos No
(dc.identifier.wos)
WOS:001231041700003
Veritabanları
(dc.source.platform)
Wos
Veritabanları
(dc.source.platform)
Scopus
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