Journal of the Optical Society of Korea

Optical Society of Korea (한국광학회)
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Adaptive Detection of a Moving Target Undergoing Illumination Changes against a Dynamic Background

  • Lu, Mu (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences) ;
  • Gao, Yang (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences) ;
  • Zhu, Ming (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences)
  • Received : 2016.08.11
  • Accepted : 2016.11.28
  • Published : 2016.12.25
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Abstract

A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.

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References

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