| Title |
Parking Control System with Fake License Plate Classification Model using Image Channel Conversion Method |
| Authors |
신준혁(Joonhyeok Shin) ; 이지영(Jiyoung Lee) ; 한서우(Seowoo Han) |
| DOI |
https://doi.org/10.5573/ieie.2023.60.8.15 |
| Keywords |
Parking control system; Object detection; Computer vision; HLS channel |
| Abstract |
The paper proposes an innovative parking control system that uses deep learning to detect fake license plate, which is a significant problem in the parking industry. The system combines a classification model that detects fake and an object detection model that detects vehicles and license plates by converting license plate images into HLS channels and separating them into Hue channels. The fake license plate sample used in this experiment is limited to paper license plate. The experimental results show the 97 percent accurate and demonstrate the effectiveness of the proposed system in preventing vehicles with fake license plates from entering the parking lot. The paper also highlights the importance of using advanced technology to address the limitations of traditional methods for detecting fake license plate. Overall, the paper makes a valuable contribution to the field of parking control systems and showcases the potential of deep learning techniques in improving security and efficiency in the parking industry. |