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

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 t...

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Bibliographic Details
Main Author: Teresa PAMUŁA
Format: Article
Language:English
Published: Silesian University of Technology 2016-09-01
Series:Scientific Journal of Silesian University of Technology. Series Transport
Subjects:
Online Access:http://sjsutst.polsl.pl/archives/2016/vol92/101_SJSUTST92_2016_Pamula.pdf
Description
Summary: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.
ISSN:0209-3324
2450-1549