The application of a CICA Neural Network on Farsi license plates recognition

Author

Akhtari, Mojdeh ; Faez, Karim

Author_Institution

Dept. of Elec., Comp. & IT, Qazvin Islamic Azad Univ., Qazvin, Iran

fYear

2010

fDate

23-25 Aug. 2010

Firstpage

205

Lastpage

208

Abstract

In this paper a new license plates recognition method using a Neural Network, trained by Chaotic Imperialistic Algorithms (CICA), is introduced. In this paper the background of the plate image is omitted, the characters are separated, and then the features of the characters are extracted. The features vector is feed into a multi layered perception neural network trained by CICA. Our dataset include 250 Farsi license plate images for train and 50 images for test in which the test images were noisy. The empirical results of the CICA-NN for license plate recognition are compared with the PSO-NN, GA-NN and MLP neural network. The results show that our method is faster and more accurate than the other methods.

Keywords

genetic algorithms; image recognition; multilayer perceptrons; particle swarm optimisation; traffic information systems; CICA neural network; Farsi license plates recognition; GA-NN; PSO-NN; chaotic imperialistic algorithms; multi layered perception neural network; Algorithm design and analysis; Artificial neural networks; Feature extraction; Gallium; Licenses; Signal processing algorithms; Training; Chaotic Imperialist Competitive Algorithm; Feature Extraction; License Plate Recognition; Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Hybrid Intelligent Systems (HIS), 2010 10th International Conference on

Conference_Location

Atlanta, GA

Print_ISBN

978-1-4244-7363-2

Type

conf

DOI

10.1109/HIS.2010.5600081

Filename

5600081