Accurate moving cast shadow suppression based on local color constancy detection

Ariel Amato, Mikhail G. Mozerov, Andrew D. Bagdanov, Jordi Gonzalez

Research output: Contribution to journalArticleResearchpeer-review

58 Citations (Scopus)


This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions. © 2011 IEEE.
Original languageEnglish
Article number5739113
Pages (from-to)2954-2966
JournalIEEE Transactions on Image Processing
Publication statusPublished - 1 Oct 2011


  • Color constancy
  • motion detection
  • shadow removal


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