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3rd International Conference on Artificial Intelligence, Machine Learning and Big Data

Copenhagen, Denmark

Farah Nabillah Abdul Razak

University Putra Malaysia, Malaysia


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Title: Malaysia License Plate Recognition Based On Deep Learning

Biography

Biography: Farah Nabillah Abdul Razak

Abstract

License plate has been the most important feature in variety of application for example in security and in traffic regulation. Recognizing the license plate research have been conducted for all these application and the data of the license plate can be found either at the toll station or even in parking lot. The important part in detecting vehicle plate is accuracy, speed and the use of limited bandwidth. There are several issues in detecting and recognizing the license plate as the feature of the license plate varies in term of the size of the plate, different standard of license plate and the colour of the license plate. Various technique have been used in detecting the license plate especially in conventional image processing. Conventional image processing involve in thresholding, detection, segmentation and recognition. But there are limitation in conventional image processing. The system use a very complex algorithm and the data have a problem with a illumination and previous work usually keep some parameter constant in order to detect and recognize the license plate. While the conventional image processing lack in the accuracy regarding the illumination, deep learning being used to ease the complexity of the algorithm in the license plate recognition.  One of the feature is Deep learning where the data can process al large number of data and the data can be trained and test. Neural network have been chosen as the main feature in detecting and recognizing the license plate