access icon free Improved license plate localisation algorithm based on morphological operations

© The Institution of Engineering and Technology
Received 18/07/2017, Accepted 07/02/2018, Revised 29/01/2018, Published 09/02/2018

Automatic license plate recognition (ALPR) systems have become an important tool to track stolen cars, access control, and monitor traffic. ALPR system consists of locating the license plate in an image, followed by character detection and recognition. Since the license plate can exist anywhere within an image, localisation is the most important part of ALPR and requires greater processing time. Most ALPR systems are computationally intensive and require a high-performance computer. The present algorithm differs significantly from those utilised in previous ALPR technologies by offering a fast algorithm, composed of structural elements which more precisely conducts morphological operations within an image, and can be implemented in portable devices with low computation capabilities. The present algorithm is able to accurately detect and differentiate license plates in complex images. This method was first tested through MATLAB with an on-line public database of Greek number plates and was 100% accurate in all clear images, and achieved 98.45% accuracy when using the entire database which included complex backgrounds and license plates obscured by shadow and dirt. Second, the efficiency of the algorithm was tested in devices with low computational processing power, by translating the code to Python, and was 300% faster than previous work.

Inspec keywords: traffic engineering computing; road vehicles; image recognition

Other keywords: access control; online public database; ALPR systems; improved license plate localisation algorithm; MATLAB; monitor traffic; portable devices; high-performance computer; automatic license plate recognition; track stolen cars; character recognition; morphological operations; character detection; structural elements; Greek number plates

Subjects: Computer vision and image processing techniques; Image recognition; Traffic engineering computing

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