A Low-Cost Real-Time Embedded Vehicle Counting and Classification System for Traffic Management Applications

被引：0

作者：

Pico, Lisseth C. ^{[1
]}

Benitez, Diego S. ^{[1
]}

机构：

[1] USFQ, Colegio Ciencias & Ingn Politecn, Campus Cumbaya,Casilla Postal 17-1200-841, Quito, Ecuador

来源：

2018 IEEE COLOMBIAN CONFERENCE ON COMMUNICATIONS AND COMPUTING (COLCOM) | 2018年

关键词：

vehicle detection; vehicle classification; ARM; Odroid-XU4;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper explores the feasibility of using a low-cost embedded ARM-based system for real-time vehicle detection, classification and counting through image processing algorithms with the aim of knowing information about vehicular traffic in different roads and highways to improve the management of mobility and the functioning of cities. This paper proposes the implementation of a low cost system to identify and classify vehicles using an Embedded ARM based platform (ODROID XU4) with Ubuntu operating system. The algorithms used are based on the Open-source library (Intel OpenCV) and implemented in Python programming language. The experimentation carried out proved that the efficiency of the algorithm implemented was 95.35 %, but it can be improved by increasing the training sample.

引用

页数：6

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