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Title: | Hybrid Proposed Model for Automatic License Plate Recognition and Distinction (ALPRD) |
Authors: | Abdulbaqi, Azmi Mosslah, Abd |
Keywords: | Artificial Neural Networks Feature Extraction Genetic Algorithm, NNGA |
Issue Date: | Jun-2016 |
Publisher: | Journal of Information, Communication |
Abstract: | This paper provides the overview of proposed Hybrid Model to construct a method to distinction between all types of cars plate's numbers. Plate's distinction system (PDS) for public, private and governmental cars plates' numbers identification and verification by using neural networks and genetic algorithm (NNGA) is proposed. This proposed algorithm demonstrated its efficiency and accuracy through the satisfactory results. It was proved a higher performance of the results. The model consists of three phases. The first phase applied the pre-processing over the plate number images. The second phase is extract the features of inputted plate, which will be passes as nodes of neural network .The third phase is pass the result of neural network to the genetic algorithm and then classify the output of cars plates numbers as private or public and governmental plates . |
URI: | http://localhost:8080/xmlui/handle/123456789/110 |
ISSN: | 19948638/26640600 |
Appears in Collections: | قسم التفسير وعلوم القرأن |
Files in This Item:
File | Description | Size | Format | |
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Hybrid Proposed Model for Automatic License Plate Recognition and Distinction (ALPRD).pdf | 1.04 MB | Adobe PDF | View/Open |
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