Abstract:
Automated license plate recognition is important in many contexts like security and law enforcement, monitoring vehicles, automated parking control, etc. To enable these automated services, we are reviewing and combining several established methods in this paper. There were three steps involved in reading car license plates: plate detection, plate extraction, and character recognition. Each stage has many sub-steps. For every sub-step, we have reviewed many methods, and chosen the one that proved to be the best solution after thorough testing and observation. The main objective of this research is to gain high accuracy using as less CPU Time as possible, keeping into consideration the facts like- lighting conditions, vehicle motion, noisy plates, and segmented words in the input image. Our primary target of this thesis is to extract a clean image of license plates of private or community vehicles. Although we target our system to be able to detect standard license plates, we also tested our methods on non-standard plates.