ICTACT Journal on Image and Video Processing

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Automatic License Plate Recognition Using Image Processing and Neural Network


Affiliations
1 Department of Electrical and Electronics Engineering, PES Institute of Technology, India
     

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In recent times, the number of vehicles on road has exponentially risen due to which traffic congestion and violations are a menace on roads. Automatic License Plate Recognition system can be used to automate the process of traffic management thereby easing out the flow of traffic and strengthening the access control systems. In this paper, we compare the efficiency achieved by morphological processing and edge processing algorithms. A detailed analysis and optimization of neural network parameters such as regularization parameter, number of hidden layer units and number of iterations is done. Here, a scheme is designed for implementation in real time and controlled using a graphical user interface suitable for the application of parking security in offices, institutions, malls, etc. The system utilizes image processing techniques and machine learning algorithms running on matlab and Raspberry Pi 2B to obtain the results with an efficiency of 97%.

Keywords

License Plate Recognition, Edge Processing, Vertical Projection, Horizontal Projection, Neural Network, Back Propagation Algorithm.
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  • Automatic License Plate Recognition Using Image Processing and Neural Network

Abstract Views: 384  |  PDF Views: 7

Authors

P. Surekha
Department of Electrical and Electronics Engineering, PES Institute of Technology, India
Pavan Gurudath
Department of Electrical and Electronics Engineering, PES Institute of Technology, India
R. Prithvi
Department of Electrical and Electronics Engineering, PES Institute of Technology, India
V. G. Ritesh Ananth
Department of Electrical and Electronics Engineering, PES Institute of Technology, India

Abstract


In recent times, the number of vehicles on road has exponentially risen due to which traffic congestion and violations are a menace on roads. Automatic License Plate Recognition system can be used to automate the process of traffic management thereby easing out the flow of traffic and strengthening the access control systems. In this paper, we compare the efficiency achieved by morphological processing and edge processing algorithms. A detailed analysis and optimization of neural network parameters such as regularization parameter, number of hidden layer units and number of iterations is done. Here, a scheme is designed for implementation in real time and controlled using a graphical user interface suitable for the application of parking security in offices, institutions, malls, etc. The system utilizes image processing techniques and machine learning algorithms running on matlab and Raspberry Pi 2B to obtain the results with an efficiency of 97%.

Keywords


License Plate Recognition, Edge Processing, Vertical Projection, Horizontal Projection, Neural Network, Back Propagation Algorithm.

References