An effective hough transform based track initiation

Shu Ling Jin, Yan Liang, Peng He, Guang Lin Pan, Quan Pan, Yong Mei Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper, a Hough Transform (HT) based track initiation method is proposed to detect targets in 3L (low signal-to-clutter-ratio, low signal-to-noise-ratio, and low detection probability) environment using a new and effective accumulation method. In the new accumulation method, the contributions of each cell's votes are determined by the neighbors of the resolving cell, instead of just the cell itself so that the disturbance of sampled probability density, due to finite samples, can be smoothed. Simulation results show that our method not only makes significant improvement in reducing false tracks but also has stronger robustness to measurement noise and clutters, compared with standard HT based track initiation with binary accumulation.

Original languageEnglish
Title of host publicationProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Pages3196-3200
Number of pages5
DOIs
StatePublished - 2006
Event2006 International Conference on Machine Learning and Cybernetics - Dalian, China
Duration: 13 Aug 200616 Aug 2006

Publication series

NameProceedings of the 2006 International Conference on Machine Learning and Cybernetics
Volume2006

Conference

Conference2006 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityDalian
Period13/08/0616/08/06

Keywords

  • Hough transform
  • Multiple target tracking
  • Track initiation

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