An efficient cast shadow removal for motion segmentation

  • Authors:

  • Byung Eun Lee;Thanh Binh Nguyen;Sun Tae Chung

  • Affiliations:

  • School of Electronics Engineering, SoongSil University, Seoul, South Korea;School of Electronics Engineering, SoongSil University, Seoul, South Korea;School of Electronics Engineering, SoongSil University, Seoul, South Korea

  • Venue:
  • ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
  • Year:
  • 2009

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Abstract

Accompanied by the rapid development of Computer Vision, Visual surveillance has achieved great evolution with more and more complicated processing. However there are still many problems to be resolved for robust and reliable visual surveillance and the cast shadow occurring in motion detection process is one of them. Shadow pixels are often misclassified as object pixels so that they cause errors in localization, segmentation, tracking and classification of objects. This paper proposes a novel cast shadow removal method. As opposed to previous conventional methods, which considers pixel properties like intensity properties, color distortion, HSV color system, and etc., the proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the background scene. Then, the product of the outcomes of application determines whether the blob pixels in the foreground mask comes from object blob regions or shadow regions. The proposed method is simple but turns out practically very effective for Gaussian Mixture Model, which is verified through experiments.