Automatic Number Plate Recognition System: A Histogram Based Approach

In past few decades number of vehicles has increased drastically. So it has become a challenging job to tract them. Even it has become seemingly impossible to identify the car owner in case of violation of any traffic rule or too fast driving. With the explosion in number of vehicles flying on the roads, proper tracking is impossible to be fully managed and monitored by humans; examples are so many like traffic monitoring, tracking stolen cars, managing parking toll, red-light violation enforcement, border and customs checkpoints. Therefore, there is a need to develop Automatic Number Plate Recognition (ANPR) system as a one of the solutions to this problem. Yet it's a very challenging problem, due to the diversity of plate formats, different scales, rotations and non-uniform illumination conditions during image acquisition. The proposed method suggests a histogram based approach which is easily implementable using MATLAB and can duly be verified for it's functionality. This approach has a basic advantage of being simple and hence faster. This paper makes use of various algorithms in each category from distinct edge detection to region of interest extraction. This enhances the performance of the system up to the maximum extent possible with less efforts and use of computational resources.