Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle

Authors

  • Chung-Hee Lee Daegu Gyeongbuk Institute of Science & Technology(DGIST)
  • Young-Chul Lim Daegu Gyeongbuk Institute of Science & Technology(DGIST)
  • Dongyoung Kim Daegu Gyeongbuk Institute of Science & Technology(DGIST)
  • Kyu-Ik Sohng Kyungpook National University

DOI:

https://doi.org/10.5755/j01.eee.20.9.3734

Keywords:

Intelligent vehicle, image segmentation, object recognition, stereo image processing

Abstract

Despite significant progress in vehicle detection over the last few decades, vehicle detection performance in heavy traffic is still inadequate. In this paper, we propose a new algorithm for vehicle detection in heavy traffic to improve detection performance. It uses two proposed segmentation methods, namely, the disparity map-based bird's-eye-view mapping segmentation method and the edge distance weighted conditional random field (CRF)-based segmentation method. Our experimental results show that the proposed algorithm outperforms conventional algorithms. The improvements in performance range from 10.8 % to 20.5 % increase in F-measure.

DOI: http://dx.doi.org/10.5755/j01.eee.20.9.3734

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Published

2014-11-05

How to Cite

Lee, C.-H., Lim, Y.-C., Kim, D., & Sohng, K.-I. (2014). Improved Vehicle Detection Algorithm in Heavy Traffic for Intelligent Vehicle. Elektronika Ir Elektrotechnika, 20(9), 54-58. https://doi.org/10.5755/j01.eee.20.9.3734

Issue

Vol. 20 No. 9 (2014)

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY

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