An Approach to Recognize Characters using Neural Network in LPR System

Abstract
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Automatic license plate recognition system is an image processing technology used to identify vehicles by their license plates. Such systems require the recognition of characters from the plate image. Artificial neural networks are commonly used to perform character recognition due to their high noise tolerance. Feed-Forward Neural Network (FFNN) can be used to recognize the characters from images. The document is expected to serve as a resource for learners in pattern recognition, neural networking and related disciplines.

Published In : IJCAT Journal Volume 1, Issue 7

Date of Publication : 31 August 2014

Pages : 367 - 370

Figures :05

Tables : 01

Publication Link : An Approach to Recognize Characters using Neural Network in LPR System

Sawender Singh : Computer Science & Engineering Department, SVIET, Banur, Punjab, 140601, India

Manveer Kaur : Computer Science & Engineering Department, SVIET, Banur, Punjab, 140601, India

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A simplistic approach for recognition of characters using artificial neural networks has been described. The advantages of neural computing over classical methods have been outlined. Despite the computational complexity involved, artificial neural networks offer several advantages in pattern recognition and classification in the sense of emulating adaptive human intelligence to a small extent. In this paper, we analyzed the character recognition phase with logsig transfer function. This work can be further extended to compare the results of different transfer functions like radbas, logsig, tansig etc.

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