Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5
Parking space recognition is an important part in the process of automatic parking, and it is also a key issue in the research field of automatic parking technology. The parking space recognition process was studied based on vision and the YOLOv5 target detection algorithm. Firstly, the fisheye came...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/15/3374 |
| _version_ | 1797586901671084032 |
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| author | Xin Zhang Wen Zhao Yueqiu Jiang |
| author_facet | Xin Zhang Wen Zhao Yueqiu Jiang |
| author_sort | Xin Zhang |
| collection | DOAJ |
| description | Parking space recognition is an important part in the process of automatic parking, and it is also a key issue in the research field of automatic parking technology. The parking space recognition process was studied based on vision and the YOLOv5 target detection algorithm. Firstly, the fisheye camera around the body was calibrated using the Zhang Zhengyou calibration method, and then the corrected images captured by the camera were top-view transformed; then, the projected transformed images were stitched and fused in a unified coordinate system, and an improved image equalization processing fusion algorithm was used in order to improve the uneven image brightness in the parking space recognition process; after that, the fused images were input to the YOLOv5 target detection model for training and validation, and the results were compared with those of two other algorithms. Finally, the contours of the parking space were extracted based on OpenCV. The simulations and experiments proved that the brightness and sharpness of the fused images meet the requirements after image equalization, and the effectiveness of the parking space recognition method was also verified. |
| first_indexed | 2024-03-11T00:28:44Z |
| format | Article |
| id | doaj.art-bfec7b63296d4ada9f88bee4b79413c1 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T00:28:44Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-bfec7b63296d4ada9f88bee4b79413c12023-11-18T22:50:06ZengMDPI AGElectronics2079-92922023-08-011215337410.3390/electronics12153374Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5Xin Zhang0Wen Zhao1Yueqiu Jiang2School of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, ChinaParking space recognition is an important part in the process of automatic parking, and it is also a key issue in the research field of automatic parking technology. The parking space recognition process was studied based on vision and the YOLOv5 target detection algorithm. Firstly, the fisheye camera around the body was calibrated using the Zhang Zhengyou calibration method, and then the corrected images captured by the camera were top-view transformed; then, the projected transformed images were stitched and fused in a unified coordinate system, and an improved image equalization processing fusion algorithm was used in order to improve the uneven image brightness in the parking space recognition process; after that, the fused images were input to the YOLOv5 target detection model for training and validation, and the results were compared with those of two other algorithms. Finally, the contours of the parking space were extracted based on OpenCV. The simulations and experiments proved that the brightness and sharpness of the fused images meet the requirements after image equalization, and the effectiveness of the parking space recognition method was also verified.https://www.mdpi.com/2079-9292/12/15/3374parking space identificationimage equalization processingimage mosaic fusionYOLOv5parking extraction |
| spellingShingle | Xin Zhang Wen Zhao Yueqiu Jiang Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 Electronics parking space identification image equalization processing image mosaic fusion YOLOv5 parking extraction |
| title | Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 |
| title_full | Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 |
| title_fullStr | Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 |
| title_full_unstemmed | Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 |
| title_short | Study on Parking Space Recognition Based on Improved Image Equalization and YOLOv5 |
| title_sort | study on parking space recognition based on improved image equalization and yolov5 |
| topic | parking space identification image equalization processing image mosaic fusion YOLOv5 parking extraction |
| url | https://www.mdpi.com/2079-9292/12/15/3374 |
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