TY - GEN
T1 - Design and Implementation of License Plate Positioning Algorithm based on FPGA
AU - Lou, Qianwen
AU - Peng, Xiwei
AU - Gao, Haizhi
AU - Feng, Xiaoxing
AU - Li, Ze
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Compared to image processing platforms such as CPU and GPU, FPGA have advantages in terms of real-time performance. The license plate positioning method based on Field Programmable Gate Array (FPGA) proposed in this paper only takes 13ms to process a frame of 640∗480 images, which takes 19ms based on GPU and 58ms based on CPU[1]. The image preprocessing method of binarization by single-channel color requires a high degree of chromaticity of the license plate part in the image. Especially when the color of the license plate is similar to the car body color, the recognition accuracy is very low. The method of binarization using two-channel mask proposed in this paper can effectively improve the accuracy of license plate recognition when the color of the license plate is similar to that of the car body or the chroma of the license plate is insufficient. Because in the actual installation of the license plate, there are four rivets on the upper and lower edges. So in the image after Sobel edge detection, the rivets affect the completeness of the upper and lower edges, resulting in irregular lines on the upper and lower edges of the license plate. When using the traditional pole method to locate the upper and lower boundaries, the error is more than 12%. When using the three-order matrix method proposed in this paper to locate the boundaries of the license plate, the error value of the four boundaries is no more than 5%, compared with the manually calibrated coordinates.
AB - Compared to image processing platforms such as CPU and GPU, FPGA have advantages in terms of real-time performance. The license plate positioning method based on Field Programmable Gate Array (FPGA) proposed in this paper only takes 13ms to process a frame of 640∗480 images, which takes 19ms based on GPU and 58ms based on CPU[1]. The image preprocessing method of binarization by single-channel color requires a high degree of chromaticity of the license plate part in the image. Especially when the color of the license plate is similar to the car body color, the recognition accuracy is very low. The method of binarization using two-channel mask proposed in this paper can effectively improve the accuracy of license plate recognition when the color of the license plate is similar to that of the car body or the chroma of the license plate is insufficient. Because in the actual installation of the license plate, there are four rivets on the upper and lower edges. So in the image after Sobel edge detection, the rivets affect the completeness of the upper and lower edges, resulting in irregular lines on the upper and lower edges of the license plate. When using the traditional pole method to locate the upper and lower boundaries, the error is more than 12%. When using the three-order matrix method proposed in this paper to locate the boundaries of the license plate, the error value of the four boundaries is no more than 5%, compared with the manually calibrated coordinates.
KW - FPGA
KW - License Plate Positioning
KW - Projection
KW - Sobel Edge Detection
KW - Two-channel Masking
UR - http://www.scopus.com/inward/record.url?scp=85203708907&partnerID=8YFLogxK
U2 - 10.1109/ICMA61710.2024.10633140
DO - 10.1109/ICMA61710.2024.10633140
M3 - Conference contribution
AN - SCOPUS:85203708907
T3 - 2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024
SP - 537
EP - 542
BT - 2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE International Conference on Mechatronics and Automation, ICMA 2024
Y2 - 4 August 2024 through 7 August 2024
ER -