EXPLORE PUBLICATIONS BY COUNTRIES

Pattern Recognition, Car Plate Recognition, Speed Tracking, Optical Character Recognition (OCR), Machine Learning, Image Processing.

The transportation challenges experienced in major cities as a result of influx of people in search of greener pastures is increasing on a daily basis. This results in an increase in the number of cars plying and competing for driving space on narrow roads. Many drivers violate traffic laws as a result of this and how to prosecute them without chasing them remains an issue to be addressed. Therefore, this research presents a model that can be used to solve this challenge using machine learning algorithms. The model consists of recognition modules such as image acquisition, Gaussian blur, localization of car plate, character segmentation and optical character recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated to track the speed of any moving object within its range of focus. The performance of the model was evaluated using metrics such as recognition accuracy, positive prediction value, negative prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.