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Smart city article details
| Title | Parking Detection Method Using Quadtree Decomposition Analysis |
|---|---|
| ID_Doc | 41307 |
| Authors | Shaaban K.; Tounsi H. |
| Year | 2022 |
| Published | Journal of Traffic and Transportation Engineering (English Edition), 9, 4 |
| DOI | http://dx.doi.org/10.1016/j.jtte.2021.10.002 |
| Abstract | Searching for available parking spaces can be a painful experience for drivers due to driving around until finding a vacant space. This study proposes a new method to automatically detect available parking spaces. The proposed system identifies empty parking spaces using grayscale images obtained from any type of video camera. The method was found to successfully identify parking availability under different conditions and scenarios. The method was tested using real-life data and achieved a detection rate of 99.7%. This method can be applied in real-time to monitor parking availability and guide drivers to empty spaces. The method has several advantages, including simple algorithms, the use of low-quality black and white images, and simple configuration. Therefore, the system can provide enormous cost savings for locations with existing black and white surveillance cameras instead of replacing existing cameras with new high-quality cameras. © 2021 Periodical Offices of Chang’an University |
| Author Keywords | Image detection; Image processing; Outdoor parking; Parking detection; Smart cities; Traffic engineering |
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