ON-ROAD VEHICLE DETECTION USING EVOLUTIONARY GABOR FILTER OPTIMIZATION

In this paper, the authors use a set of Gabor filters, specifically optimized for vehicle detection, for improving the performance of on-road vehicle detection. They propose a systematic and general evolutionary Gabor filter optimization (EGFO) approach to optimize the parameters of a set of Gabor filters to be used in the context of vehicle detection. Focus is on building a set of filters that can more strongly respond to features present in vehicles than to non-vehicles, thus improving class discrimination. Using the EGFO approach, filter design is integrated with filter selection by integrating genetic algorithms (GAS) with an incremental clustering approach.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  Operations Center, 445 Hoes Lane, P.O. Box 1331
  Piscataway, NJ  United States  08855-1331
• Authors:
  • Sun, Z
  • Bebis, G
  • Miller, R
• Publication Date: 2005-6

Language

• English

Media Info

• Features: Figures; Photos; References; Tables;
• Pagination: pp 125-137
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 6
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Automatic vehicle location; Image processing; Optical detectors; Vehicle detectors; Video imaging detectors
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01005289
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: BTRIS, TRIS
• Created Date: Oct 14 2005 8:25AM