Labeling Algorithm and Fully Connected Neural Network for Automated Number Plate Recognition System

Alexander, Kevin and Wicaksana, Arya and Iswari, Ni Made Satvika (2019) Labeling Algorithm and Fully Connected Neural Network for Automated Number Plate Recognition System. ACIT 2019: Applied Computing and Information Technology. pp. 129-145.

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Abstract

Applications of automated number plate recognition (ANPR) technology in the commercial sector has developed rapidly in recent years. The applications of ANPR system such as vehicle parking, toll enforcement, and traffic management are already widely used but not in Indonesia today. In this paper, the Labeling algorithm and a fully connected neural network are used to create an ANPR system for vehicle parking management in Universitas Multimedia Nusantara, Indonesia. The system is built using Java and the Android SDK for the client and PHP for the server. The proposed ANPR system is targeted for Indonesian civilian number plate. Testing shows that the ANPR system has been implemented successfully. Evaluation of the system gives a precision value of 1 and a recall value of 0.78. These values are obtained with hidden layer nodes of 75, 85, and 95. These number of hidden nodes delivers an F-score of 0.88 with the accuracy of 88%.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming
300 Social Sciences > 380 Commerce, communications and transportation > 388 Transportation (Road, Vehicle, Parking Facilities)
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 11 Oct 2021 13:27
Last Modified: 11 Oct 2021 13:27
URI: http://kc.umn.ac.id/id/eprint/18652

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