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  • 标题:Real-Time System Based on Feature Extraction for Vehicle Detection and Classification
  • 本地全文:下载
  • 作者:Zakaria Moutakki ; Imad Mohamed Ouloul ; Karim Afdel
  • 期刊名称:Transport and Telecommunication Journal
  • 印刷版ISSN:1407-6160
  • 电子版ISSN:1407-6179
  • 出版年度:2018
  • 卷号:19
  • 期号:2
  • 页码:93-102
  • DOI:10.2478/ttj-2018-0008
  • 语种:English
  • 出版社:Walter de Gruyter GmbH
  • 摘要:Today, Road traffic video surveillance becomes the centre of several concerns. It presents an important way for analysis of road traffic in highways. Road traffic video surveillance can help to resolve many problems which can influence road safety. This paper presents a real-time management and control system which serve to analyze road traffic using a stationary camera. The proposed system can measure the quantity and characteristics of traffic in real time based on three modules, segmentation, classification and vehicle counting. Our contribution consists of developing a feature-based counting system for vehicle detection and recognition under the conditions which present a challenge in recent systems, such as occlusions, and illumination conditions. Our method can perform vehicle detection and classification by eliminating the influence of many factors on system efficiency. The obtained results show that the system proposed in this paper provides a counting rate higher than that of some existing methods.
  • 关键词:Intelligent transportation systems ; Vehicle detection ; Occlusion handling ; Vehicle classification ; Background subtraction ; Feature extraction
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