Removing Shadows from Images

  • Graham D. Finlayson
  • Steven D. Hordley
  • Mark S. Drew
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2353)


Illumination conditions cause problems for many computer vision algorithms. In particular, shadows in an image can cause segmentation, tracking, or recognition algorithms to fail. In this paper we propose a method to process a 3-band colour image to locate, and subsequently remove shadows. The result is a 3-band colour image which contains all the original salient information in the image, except that the shadows are gone.

We use the method set out in [1] to derive a 1-d illumination invariant shadow-free image. We then use this invariant image together with the original image to locate shadow edges. By setting these shadow edges to zero in an edge representation of the original image, and by subsequently re-integrating this edge representation by a method paralleling lightness recovery, we are able to arrive at our sought after full colour, shadow free image. Preliminary results reported in the paper show that the method is effective.

A caveat for the application of the method is that we must have a calibrated camera. We show in this paper that a good calibration can be achieved simply by recording a sequence of images of a fixed outdoor scene over the course of a day. After calibration, only a single image is required for shadow removal. It is shown that the resulting calibration is close to that achievable using measurements of the camera’s sensitivity functions.


Texture shading, & colour shadow removal lightness recovery illuminant invariance 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Graham D. Finlayson
    • 1
  • Steven D. Hordley
    • 1
  • Mark S. Drew
    • 2
  1. 1.School of Information SystemsThe University of East AngliaNorwichEngland
  2. 2.School of Computing ScienceSimon Fraser UniversityVancouverCanada

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