Design And Development Of A License Plate Recognition System Using Convolutional Neural Network

Eh, Zheng Yi (2016) Design And Development Of A License Plate Recognition System Using Convolutional Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text Design And Development Of A License Plate Recognition System Using Convolutional Neural Network 24 Pages.pdf - Submitted Version Download (368kB)

Abstract

The number of vehicles on the road has increased drastically in this decade. Due to this matter, the implementation of license plate recognition system is needed that can help to control and surveillance on traffic flow. But, in previous research the license plate recognition system performed low accuracy on character recognition stage. So, this research is carried out to make improvement in recognition stage. This research is to develop a license plate recognition system that used to recognize the standard Malaysian license plate characters using Convolutional Neural Network. The license plate recognition system consist of pre-processing process that can localize license plate region in a sample and follow by segment license plate character for Convolutional Neural Network recognition. Besides that, the parameters used by four layered Convolutional Neural Network are analyzed and the best Convolutional Neural Network architecture for license plate character recognition is obtained. As a result, license plate pre-processing stage achieved 74.7% accuracy and Convolutional Neural Network recognition stage achieved 94.6% accuracy.

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