CLASSIFICATION OF ROAD TRAFFIC CONDITIONS BASED ON TEXTURE FEATURES OF TRAFFIC IMAGES USING NEURAL NETWORKS

被引：2

作者：

Pamula, Teresa ^{[1
]}

机构：

[1] Silesian Tech Univ, Fac Transport, Krasinskiego 8 St, PL-40019 Katowice, Poland

来源：

SCIENTIFIC JOURNAL OF SILESIAN UNIVERSITY OF TECHNOLOGY-SERIES TRANSPORT | 2016年 / 92卷

关键词：

traffic conditions; textures features; neural networks;

D O I：

10.20858/sjsutst.2016.92.10

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

The paper presents a method of classification of road traffic conditions based on the analysis of the content of images of the traffic flow. The view of the traffic lanes with vehicles is treated as a texture, while the change in the description of its characteristics is ascribed to the change in the density of traffic. Four classes of conditions are determined on the basis of the values of Haralick texture features. An MLP network is used for classification. Video data, which were registered by an UAV hanging over a traffic junction, are used for validation of the method.

引用

下载

页码：101 / 109

页数：9

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