FUSION OF WAVELET TRANSFORM AND COLOR INFORMATION FEATURES FOR AUTOMATIC VEHICLE REIDENTIFICATION IN INTELLIGENT TRANSPORTATION SYSTEMS

This paper presents a fusion-based vehicle reidentification system algorithm that uses 4 different features to achieve high accuracy: 1) the wavelet transform of the inductive signature vector acquired from loop detectors; 2) vehicle velocity; 3) traversal time; and 4) color information based on images acquired from video cameras. A nearest neighbor approach classifies the features, and linear feature fusion is shown to improve performance. With the fusion of 4 features, more than a 92% accuracy was obtained on real data collected from a parkway in California. Also, it was found that the wavelet transform improves performance and reduces the dimension of the feature vector when compared to the raw vehicle signatures.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/0780384849
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Arr, G A
  • Sun, Chao
  • Ramachandran, R R
• Conference:
  • 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • Location: Montreal, Canada
  • Date: 2004-5-17 to 2004-5-19
• Publication Date: 2004

Language

• English

Media Info

• Features: References;
• Pagination: p. 285-288
• Serial:
  • Volume: 5

Subject/Index Terms

• TRT Terms: Algorithms; Automated highways; Character recognition; Image analysis; Image processing; Integral transforms; Intelligent transportation systems; Tracking systems; Traffic data; Traffic density; Traffic engineering; Travel time; Wavelets
• Uncontrolled Terms: Nearest neighbor approach; Vehicle tracking
• Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 00979121
• Record Type: Publication
• ISBN: 0780384849
• Files: TRIS
• Created Date: Sep 20 2004 12:00AM