@inproceedings{ee320d81412e4c55ae58a8a422d84f27,
title = "A real-time vehicle identification system implemented on an embedded ARM platform",
abstract = "This paper explores the feasibility of using a low-cost embedded ARM-based system for real-time vehicle recognition and identification through image processing. The main features of the system include: vehicle detection, speed measurement, and vehicle identification by license plate number recognition, the information obtained is then send to a database on a server in a local network. An ODROID-U3 embedded board was used for general processing and control. Image processing algorithms for detection of moving vehicles on a road were implemented and optimized, in order to obtain shorter processing times than existing algorithms. OpenCV libraries were used for the implementation. Finally, an analysis of the processing times required by the algorithms and the error percentages obtained with the system implemented are presented and discussed.",
keywords = "ARM, ODROID-U3, Speed determination, Vehicle identification",
author = "Danny Sotomayor and Ben{\'i}tez, \{Diego S.\} and Rosero, \{Milton F.\} and Paola Leon",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 ; Conference date: 18-10-2017 Through 20-10-2017",
year = "2017",
month = dec,
day = "19",
doi = "10.1109/CHILECON.2017.8229670",
language = "Ingl{\'e}s",
series = "2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--7",
booktitle = "2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings",
}