License plate recognition of moving vehicles

Pattern recognition has been identified by researchers as one of the neural network applications. There are many researches on this topic whether it character recognition or other pattern. The famous application in pattern recognition is the character recognition whether it handwritten recognitio...

Full description

Saved in:
Bibliographic Details
Main Author: Siti Rahimah, Abd Rahim
Format: Final Year Project Report
Language:English
English
Published: Universiti Malaysia Sarawak, UNIMAS 2010
Subjects:
Online Access:http://ir.unimas.my/id/eprint/4585/1/License%20Plate%20Recognition%20of%20Moving%20Vehicles%20%2824pgs%29.pdf
http://ir.unimas.my/id/eprint/4585/8/SIT1%20RAHIMAH.pdf
http://ir.unimas.my/id/eprint/4585/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Malaysia Sarawak
Language: English
English
Description
Summary:Pattern recognition has been identified by researchers as one of the neural network applications. There are many researches on this topic whether it character recognition or other pattern. The famous application in pattern recognition is the character recognition whether it handwritten recognition or others such as Arabic and Chinese character. In this project, the character recognition is for moving vehicles where character from license plate of moving vehicles will be recognized. License plate character consists of alphabet and number. Incorporated with image processing and neural network toolbox, this simulation will be design using the MATLAB toolbox. This project consists of two parts where the image will be process in image processing part while the character will be recognized using the backpropagation neural network. The character recognition will be recognizing according to the target output. In addition, performing recognition simulations compare between 50 and 100 neuron of hidden layer for the best character recognition. At the end of this project the recognized character from the license plate will be presented.