Vehicle Detection and Classification Using Model-Based and Fuzzy Logic Approaches

Vehicle detection and classification information is invaluable in many transportation issues. Vehicle feature extraction and detection are the preprocesses required for vehicle classification. Current automatic vehicle classification systems have deficiencies: low accuracy, special requirements, fixed orientation of the camera, or additional hardware and devices. This paper discusses a vehicle detection and classification system using model-based and fuzzy logic approaches. The system was tested with the use of a variety of images captured by the highway traffic control center of the Utah Department of Transportation. In comparison with existing systems, major advantages of the proposed system are (a) no special orientation of the camera is required, (b) no additional devices are needed, and (c) high classification accuracy is provided. Experimental results show that the performance of the proposed system exceeds that of the existing video-based vehicle classification systems.

• Record URL:
  https://doi.org/10.3141/1935-18
• 
• Summary URL:
  http://scholar.google.com/scholar_lookup?title=Vehicle+Detection+and+Classification+Using+Model-Based+and+Fuzzy+Logic+Approaches&author=H.+Cheng&author=H.+Du&author=L.+Hu&author=C.+Glazier&publication_year=2005
• Availability:
  • Find a library where document is available. Order URL: http://www.trb.org/Main/Public/Blurbs/155479.aspx
• Authors:
  • Cheng, Heng-Da
  • Du, Haining
  • Hu, Liming
  • Glazier, Chris
• Publication Date: 2005

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 154-162
• Monograph Title: Information Systems and Technology
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 1935
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Accuracy; Algorithms; Automatic vehicle classification; Automatic vehicle detection and identification systems; Fuzzy logic; Image processing; Mathematical models; Performance
• Identifier Terms: Utah Department of Transportation
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01023225
• Record Type: Publication
• ISBN: 0309094097
• Files: TRIS, TRB, ATRI
• Created Date: Apr 25 2006 5:03PM