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Color HarmonizationDaniel Coher-Or   Olga Sorkine       Ran Gal        Tommer Leyvand,   Ying-Qing Xu                     ...
Introduction       Contributions   Results                        Critique            Ou t lin e  ●   Introduction      – ...
Introduction           Contributions     Results                Critique                    M o t iv a t io n ::C o lo r H...
Introduction       Contributions       Results                 Critique P r e v io u s Wo r k Previous applications includ...
Introduction        Contributions      Results                 Critique  P r e v io u s Wo r k  The authors utilize Ittens...
Introduction     Contributions        Results                 Critique     Im p le m e n t a t io n ::His t o g r a m M a ...
Introduction     Contributions     Results                Critique     Im p le m e n t a t io n ::His t o g r a m M a t c ...
Introduction       Contributions         Results                 Critique     Im p le m e n t a t io n ::His t o g r a m M...
Introduction      Contributions           Results                Critique            Im p le m e n t a t io n ::C o lo r S...
Introduction      Contributions             Results                Critique            Im p le m e n t a t io n ::C o lo r...
Introduction     Contributions         Results                Critique            Im p le m e n t a t io n ::C o lo r Sh i...
Introduction           Contributions        Results                 Critique                    Re s u lt s ::In t e r [ f...
Introduction       Contributions        Results                 Critique                    Re s u lt s ::A p p lic a t io...
Introduction        Contributions      Results                Critique                      Re s u lt s ::A p p lic a t io...
Introduction         Contributions      Results                Critique                       Re s u lt s ::A p p lic a t ...
Introduction     Contributions     Results                   Critique                    Re s u lt s ::Dis c u s s io n Un...
Introduction      Contributions      Results                   Critique                     Re s u lt s ::Lim it a t io n ...
Introduction   Contributions        Results                Critique                             C r it iq u eMXMLLN Montgo...
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Color Harmonization

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A presentation of Color Harmonization by Daniel Cohen-Or from Tel Aviv University for my CSci 8980 Computer Science Design class taught by Gary Meyer at the University of Minnesota in Fall 2009.

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Color Harmonization

  1. 1. Color HarmonizationDaniel Coher-Or Olga Sorkine Ran Gal Tommer Leyvand, Ying-Qing Xu Tel Aviv University, Microsoft Research Asia A MXMLLN Montgomery PresentationThe TheGreat GreatWave WaveOff OffKanagawa KanagawaHokusai Hokusai
  2. 2. Introduction Contributions Results Critique Ou t lin e ● Introduction – Motivation – Previous Work •Contributions – Histogram Matching – Color Shifting ● Results ● Applications ● Limitations ● CritiqueMXMLLN Montgomery University of Minnesota
  3. 3. Introduction Contributions Results Critique M o t iv a t io n ::C o lo r Ha r m o n y The authors define harmonic colors as sets of color that have some special order and relationship in color space resulting in a aesthetic visual appearance.MXMLLN Montgomery University of Minnesota
  4. 4. Introduction Contributions Results Critique P r e v io u s Wo r k Previous applications include mostly commercial design products that provide users with sets of harmonic colors None have the ability to harmonize an input image One solution attempts to automate part of the design process by introducing harmonic rules to assist the user. [MEIER, B.J 1988. ACE: a color expert system for user interface design.]MXMLLN Montgomery University of Minnesota
  5. 5. Introduction Contributions Results Critique P r e v io u s Wo r k The authors utilize Ittens color model where color harmony is defined as the relationships between hues on the color wheel. [Figure 2] In addition, the set of 80 color schemes defined as combinations of the 8 hue [Figure 2] and 10 tone distributions that Matsuda produced from his psychophysical experiments are the foundation of this research.MXMLLN Montgomery University of Minnesota
  6. 6. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g The main goal of Color Harmonization is to transform the color histogram of an image to match one of the eight hue distribution templates. ¿What makes the image disharmonious? ¿How would you traditionally determine the closest template? ¿Which template would you suggest?MXMLLN Montgomery University of Minnesota
  7. 7. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g Disharmonies The cyans, purples, and small amount of bright green are outliers in the predominantly dark blue and bright yellow and orange image. ¡There is no rainbow template!MXMLLN Montgomery University of Minnesota
  8. 8. Introduction Contributions Results Critique Im p le m e n t a t io n ::His t o g r a m M a t c h in g ● F(X, (m, a)) measures the harmony of the image X with respect to a scheme (m, a) ● M(X,Tm) defines the best harmonic scheme for the template Tm ● B(X) is the best harmonic scheme for the image X is the closest hue in the template Tm, oriented at angle a, to pixel p. H(p) is the hue channel S(p) is the saturation channel |·| is the arc distance on the hue wheelMXMLLN Montgomery University of Minnesota
  9. 9. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sp lit t in g Color artifacts appear if a color from the hue histogram is halfway between the template borders [Figure d] *Situation mostly arises when user inputs desired templateMXMLLN Montgomery University of Minnesota
  10. 10. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sp lit t in g Binary labeling segmentation using graph-cut optimization For each set of pixels Ω, minimize the energy E(V), the sum of the distance between the pixel hue H(p) and hue assignment H(v(p)), E1(V), and the grouping of adjacent pixels, E2(V) N is the set of neighboring pixels in Ω δ(v(p), v(q))) is 1 if labels of pixels p and q are diferent, else 0 Smax(p,q) is the greater saturation between the two pixelsMXMLLN Montgomery University of Minnesota
  11. 11. Introduction Contributions Results Critique Im p le m e n t a t io n ::C o lo r Sh if t in g After pixels are assigned a region in the template, the hues are shifted to fit in the region Density of hues is preserved around hue at the center of the region C(p) Gσ(x) ε (0, 1] with standard deviation σ and mean 0MXMLLN Montgomery University of Minnesota
  12. 12. Introduction Contributions Results Critique Re s u lt s ::In t e r [ f a c e , a c t io n ]MXMLLN Montgomery University of Minnesota
  13. 13. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s The applications for Color Harmonization are extensive Anywhere digital design tools are used, there is a place for a color harmony recommendation system Interior DesignMXMLLN Montgomery University of Minnesota
  14. 14. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s Graphic Design Harmonize with respect to foreground Harmonize with respect to backgroundMXMLLN Montgomery University of Minnesota
  15. 15. Introduction Contributions Results Critique Re s u lt s ::A p p lic a t io n s Graphic Design Harmonize with respect to color schemeMXMLLN Montgomery University of Minnesota
  16. 16. Introduction Contributions Results Critique Re s u lt s ::Dis c u s s io n Underlying algorithms give more weight to highly saturated pixels Unsaturated hues lead to less striking or noticeable resultsMXMLLN Montgomery University of Minnesota
  17. 17. Introduction Contributions Results Critique Re s u lt s ::Lim it a t io n s No support for divided or interrupted hue regionsMXMLLN Montgomery University of Minnesota
  18. 18. Introduction Contributions Results Critique C r it iq u eMXMLLN Montgomery University of Minnesota

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