Open AccessApplication of Artificial Neural Network to ANPR: An Overview
Author(s) -
Harish Paruchuri
Publication year - 2015
Publication title -
abc journal of advanced research
Language(s) - English
Resource type - Journals
eISSN - 2312-203X
pISSN - 2304-2621
DOI - 10.18034/abcjar.v4i2.549
Subject(s) - documentation , computer science , artificial neural network , artificial intelligence , function (biology) , fault detection and isolation , real time computing , computer vision , evolutionary biology , actuator , biology , programming language
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.