Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Fusion of Background Subtraction and Clustering Techniques for Shadow Suppression in Video Sequences

  • Received : 2013.04.17
  • Accepted : 2013.10.31
  • Published : 2013.10.30
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Abstract

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

Keywords

References

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