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Shadow removal

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

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  1. Shadowremoval Team F CorinaBlajovici Zoltán Bónus Péter József Kiss László Varga

  2. 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

  3. 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

  4. 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

  5. 4. Results (1/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  6. 4. Results (2/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  7. 4. Results (3/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  8. 4. Results (4/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  9. 4. Results (5/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  10. 4. Results (6/6) Additivemethod Light-modelbasedmethod Combinativemethod SSIP 2011 - Shadow removal

  11. 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

  12. 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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