Electrical Engineering, Islamic Azad University
Electrical Engineering, Islamic Azad University majlesi branch
Electerical Engineering, Islamic Azad university of Majlesi Branch
Department of Electrical Engineering, Faculty of Engineering
License plate recognition (LPR) by using morphology has the advantage of resistance to brightness changes; high speed processing, and low complexity. However these approaches are sensitive to the distance of the plate from the camera and imaging angle. Various assumptions reported in other works might be unrealistic and cause major problems in practical experiences. In this paper we considered morphological approaches and improved them by using adaptive techniques to achieve more compatibility with practical applications. We examined the developed system on several car plate image databases with different conditions like different camera distance, and different car views. The average achieved rate of success was 89.95% for car plate location recognition, which is around 6.0% higher than previous related report of morphological methods. We further implemented the system on an FPGA platform.