Moving shadow detection by nonlinear Tone-Mapping

Elad Bullkich, Idan Ilan, Yair Moshe, Yacov Hel-Or, Hagit Hel-Or

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

Abstract

Shadow detection is a well-known problem in image and video processing. Detecting moving shadows is useful in numerous applications such as object detection and tracking. Most works in this area are not suitable for shadow detection using a low-cost outdoor surveillance camera. In this work we suggest a fast shadow detection approach for video surveillance, by comparing each video frame to a continuously updated background image. We differentiate shadow areas from foreground areas by assuming the shadow pixels are associated with background pixels through a nonlinear tone mapping. This assumption is general and applies to various systems and scene conditions. A distance measure between patch images that account for nonlinear tone mapping is calculated by adapting a recently suggested approach for pattern matching termed Matching by Tone Mapping (MTM). We show that the proposed technique is computationally efficient and outperforms state-of-the-art shadow detection techniques in typical surveillance scenarios.

Original languageAmerican English
Title of host publication2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012
Pages146-149
Number of pages4
StatePublished - 2012
Event2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012 - Vienna, Austria
Duration: 11 Apr 201213 Apr 2012

Publication series

Name2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012

Conference

Conference2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012
Country/TerritoryAustria
CityVienna
Period11/04/1213/04/12

Keywords

  • shadow detection
  • visual surveillance

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

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