Application of Artificial Neural Network to ANPR: An Overview

Authors

  • Harish Paruchuri Vintech Solutions, Inc.

DOI:

https://doi.org/10.18034/abcjar.v4i2.549

Keywords:

Automatic Number Plate Recognition (ANPR), Character partitioning, Traffic flow, number plate

Abstract

Vehicle owner documentation and traffic flow mechanism have contributed to a major issue in each country. From time to time it turns out to be challenging to detect car owners who fault traffic regulations. Hence, it of interest to us to investigate designs for automatic number plate detection structure as a clarification and proffer solution to this issue. There are several automatic number plate detection or recognition structure existing today. The structure is according to diverse methods nonetheless automatic number plate recognition is still a difficult job as many of the parameters such as a fast-moving vehicle, non-uniform car number plate, the language used in writing the vehicle number and various lighting situations may hinder 100% detection rate. Many of the structure-function underneath these boundaries. This paper review diverse methods of automatic number plate recognition considering success rate, picture size, and processing time as factors.  However, automatic number plate detection is recommended for traffic regulating agencies.

 

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Author Biography

  • Harish Paruchuri, Vintech Solutions, Inc.

    Big Data Engineer, Vintech Solutions, Inc., 9715 Olive Blvd, Olivette, MO 63132, USA

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Published

2015-12-31

How to Cite

Paruchuri, H. (2015). Application of Artificial Neural Network to ANPR: An Overview. ABC Journal of Advanced Research, 4(2), 143-152. https://doi.org/10.18034/abcjar.v4i2.549

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