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Shadow removal. Team F Corina Blajovici Zoltán Bónus Péter József Kiss László Varga. 1. Our main goal. Remove shadows from pictures without user interaction Can be separeted to two different tasks :. 1 . Find the shadow (shadow mask). 2 . Remove the shadow. 2. Shadow detection.

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shadow removal

Shadowremoval

Team F

CorinaBlajovici

Zoltán Bónus

Péter József Kiss

László Varga

1 our main goal
1. Our main goal
  • Removeshadowsfrompictureswithoutuserinteraction
  • Can be separeted to two different tasks:

1. Find the shadow (shadow mask)

2.Remove the shadow

SSIP 2011 - Shadow removal

2 shadow detection
2. Shadowdetection
  • Histrogram dissension
  • Iterate through the Y channel of the picture in Ycbcr colorspace
  • Start with NxN size window, and compare intensities with the average of the whole picture and the window
  • Pixels with lower intensity will be marked as shadows
  • Repeatfromthethirdstepwithsmallerwindowsize, butonlymodifytheunmarkedpixels (untilwindowsizereaches 3x3)

SSIP 2011 - Shadow removal

3 shadow removal
3. Shadowremoval
  • We implemented 3 different algorythms forthis task:
  • Additivecorrection of shadow pixel colors
  • Light-model based color correction
  • Combination of thefirsttwoinYcbcrcolorspace

SSIP 2011 - Shadow removal

4 results 1 6
4. Results (1/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

4 results 2 6
4. Results (2/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

4 results 3 6
4. Results (3/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

4 results 4 6
4. Results (4/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

4 results 5 6
4. Results (5/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

4 results 6 6
4. Results (6/6)

Additivemethod

Light-modelbasedmethod

Combinativemethod

SSIP 2011 - Shadow removal

5 conclusions
5. Conclusions
  • ShadowRemoval is a hardtask!
  • Whatwereached, and whatstillcan be improved:
    • A systemthatcanremoveshadowfromhomogenioustexrute.
    • A segmentationapproachtodetectcrispshadowson an image.
      • Probably a ‘fuzzy’ shadowmembershiponthepixelswouldgive a betterdescription.
    • Thremethodsfortheremoval of shadows:
      • Someactuallyworksfine, but has no mathematicalbackgorund.
      • Some has a nicemathematicaldescription, butunfortunatelythe „World is notwillingtofollowthemodeltotheletter”.

SSIP 2011 - Shadow removal

final conclusions
FinalConclusions
  • Anyway, the system is not perfect, but it can work on lots of images.
  • Using it and being lucky can just work fine! 

SSIP 2011 - Shadow removal

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