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Multi-stage Automatic License Plate Location & Recognition

Since as early as 1970’s, the need of an Automatic License Plate Recognition system (ALPR) has arose based on the need to implement law enforcement and traffic control on transportation systems. This area has motivated a large amount of research effort, and various approaches and solutions have been proposed and implemented. Existing ALPR systems typically consist of modules addressing the following three tasks: license plate localization, character segmentation, and character recognition. In this paper, a novel ALPR system is proposed where a new de-skewing stage is added between license plate localization and character segmentation stages. This new stage allow the system to process images that are taken at an angle with respect to the LP’s normal and from a relatively close distance, which typically results in skew distortion. The additional stage ensures that the characters are all lined up in a horizontal line with the same height, which allows precise character segmentation; furthermore, it rectifies the characters and allows simple recognition techniques such as cross-correlation to yield good classification results. In addition to the de-skewing stage, a license plate localization method is also proposed. It shares some common ground with the current approaches, as it is based on vertical edge density. Note that images with complicated edge backgrounds have been a common problem for algorithms that use an edge density approach, while the new localization method has a success rate of 86.4% based on a database of 822 images. While at this point in time the prototype system’s LP recognition accuracy at 12.3% is not practical, several of its rudimentary technique employed could be exchanged for more sophisticated and effective ones and thus improving system performance significantly in future efforts. However, this work demonstrates that the de-skewing process can be significantly advantageous.