نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
License Plate Detection is an essential part of smart transportation systems which is always expected to be accurate and efficient. The exponential growth of the number of vehicles has led to many problems for vehicle detection in different fields such as traffic control, parking lot, toll highways and so. Using an automatic system for plate number detection of the vehicle, a large number of problems can be solved. One of the best methods for overcoming this problem is using a convolutional neural network approach. They have shown impressive performance in various computer vision tasks. In this work, we tried to introduce a new dataset of Iranian cars' plates. Then using transfer learning and Alexnet, we have proposed a new approach for detection and classifying the plate numbers. We conducted comprehensive experiments on the new dataset. The experimental results show that the proposed method has achieved to 97.35% accuracy.
کلیدواژهها English
