Character recognition of Malaysian license tender plate number using neural network / Izzwan Ishak

Ishak, Izzwan (2007) Character recognition of Malaysian license tender plate number using neural network / Izzwan Ishak. Degree thesis, Universiti Teknologi MARA.

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Abstract

In this paper, a method to recognize each characters of Malaysian License Plate Number by using Artificial Neural Network is proposed. This character recognition phase is part of the License Plate Number Recognition System which it become one of important technology that can be used for identification of vehicle all around the world. This technology is used in various security and traffic applications such as parking, access control, tolling, border control, stolen car, enforcement, traffic control, and so on. Based on the previous research which related with this paper, much character recognition is extensively implemented using Neural Network, which generally solves problems that other methods failed to solve. Beside that, many easy-to-use tools can provide the easy and convenient use of Neural Network method. In order to perform the character recognition system, all result, theory and technique of the previous project research and development based on pattern recognition will be gathered as the basic ideas and references toward project methodology and implementation. Beside that, successful task of recognition also depend on the image processing

Item Type: Thesis (Degree)
Creators:
CreatorsEmail
Ishak, IzzwanUNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Neural networks (Computer science)
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Neural networks (Computer science)

T Technology > TL Motor vehicles. Aeronautics. Astronautics > Motor vehicles. Cycles
Divisions: Faculty of Information Technology and Quantitative Sciences
Item ID: 9330
Uncontrolled Keywords: Malaysian, license, tender plate number, neural network, system
Last Modified: 26 Oct 2017 03:29
Depositing User: Staf Pendigitalan 2
URI: http://ir.uitm.edu.my/id/eprint/9330

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