Graph Cut Based Segmentation of Soft Shadows for Seamless Removal and Augmentation

  • Michael Nielsen
  • Claus B. Madsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


This paper introduces a new concept within shadow segmentation for usage in shadow removal and augmentation through construction of a multiplicity alpha overlay shadow model. Previously, an image was considered to consist of shadow and non-shadow regions. This makes it difficult to seamlessly remove shadows and insert augmented shadows that overlap real shadows. We construct a model that accounts for sunlit, umbra and penumbra regions by estimating the degree of shadow. The model is based on theories about color constancy, daylight, and the geometry that causes penumbra. A graph cut energy minimization is applied to estimate the alpha parameter. Overlapping shadow augmentation and removal is also demonstrated. The approach is demonstrated on natural complex image situations. The results are convincing, and the quality of augmented shadows overlapping real shadows and removed shadows depends on the quality of the estimated alpha gradient in penumbra.


shadow segmentation graph cuts augmented reality 


  1. 1.
    Salvador, E., Cavallaro, A., Ebrahimi, T.: Cast shadow segmentation using invariant color features. Comput. Vis. Image Underst. 95(2), 238–259 (2004), doi:10.1016/j.cviu.2004.03.008CrossRefGoogle Scholar
  2. 2.
    Madsen, C.B.: Using real shadows to create virtual ones. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, pp. 820–827. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  3. 3.
    Finlayson, G.D., Hordley, S.D., Drew, M.S.: Removing shadows from images. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 823–836. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    Finlayson, G.D., Drew, M.S., Lu, C.: Intrinsic Images by Entropy Minimization. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3023, pp. 582–595. Springer, Heidelberg (2004)Google Scholar
  5. 5.
    Lu, C., Drew, M.S.: Shadow segmentation and shadow-free chromaticity via markov random fields. In: IS&T/SID 13th Color Imaging Conference, Scottsdale, AZ (2005)Google Scholar
  6. 6.
    Finlayson, G.D., Hordley, S.D., Drew, M.S.: Removing shadows from images using retinex. In: Color Imaging Conference, pp. 73–79. IS&T - The Society for Imaging Science and Technology (2002)Google Scholar
  7. 7.
    Nielsen, M., Madsen, C.B.: Segmentation of Soft Shadows Based on a Daylight- and Penumbra Model. In: Gagalowicz, A., Philips, W. (eds.) MIRAGE 2007. LNCS, vol. 4418, pp. 341–352. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Kolmogorov, V., Zabih, R.: What energy functions can be minimized via graph cuts? IEEE Trans. Pattern Anal. Mach. Intell. 26(2), 147–159 (2004)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Michael Nielsen
    • 1
  • Claus B. Madsen
    • 1
  1. 1.Laboratory of Computer Vision and Media Technology, Aalborg UniversityDenmark

Personalised recommendations