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Art Authentication & Painting Style Classification Wan-Ting Lee Chin-Sheng Chen 5/10/2006 Multimedia Security Systems Outline Authentication Author Identification Van Gogh Style Classification Light Line Color Texture Impressionism Fauvism Cubism Discuss Experiment Result

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art authentication painting style classification

Art Authentication &Painting Style Classification

Wan-Ting Lee

Chin-Sheng Chen

5/10/2006 Multimedia Security Systems

outline
Outline
  • Authentication
    • Author Identification
      • Van Gogh
  • Style Classification
    • Light
    • Line
    • Color
    • Texture
      • Impressionism
      • Fauvism
      • Cubism
  • Discuss Experiment Result
  • References
authentication4
Authentication
  • Architecture
authentication6
Authentication
  • Feature Vectors
authentication7
Authentication
  • Feature Vectors
authentication8
Authentication
  • Hausdorff Distance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

1 0 2.5138 3.1485 2.2648 3.2077 0.3649 3.6279 2.8836 3.1286 4.8374 1.1268 1.7501 4.1207 1.9475 4.7728 1.2088 3.3849 2.0807

2 2.5138 0 0.7593 1.3405 0.9127 2.4660 1.2342 0.9155 0.8748 7.1452 2.2211 3.7787 6.5029 2.8895 7.0592 3.0610 5.7533 2.4759

3 3.1485 0.7593 0 1.3854 0.8367 3.0766 0.7638 0.7775 0.5699 7.3764 2.8485 3.6503 6.4038 2.7290 7.4651 2.9318 5.6631 2.3055

4 2.2648 1.3405 1.3854 0 1.4814 2.3037 1.8908 1.3111 1.5514 6.3835 2.3156 3.0889 5.5681 1.8293 6.5477 2.0869 4.8392 1.8396

5 3.2077 0.9127 0.8367 1.4814 0 3.1528 0.5555 0.9025 0.8777 7.4384 3.0608 4.0441 6.5157 2.4781 7.5707 3.0329 5.7923 2.5825

6 0.3649 2.4660 3.0766 2.3037 3.1528 0 3.5856 2.8271 3.0443 4.6922 0.9045 1.5982 4.0534 2.0226 4.6101 1.2382 3.2996 1.9540

7 3.6279 1.2342 0.7638 1.8908 0.5555 3.5856 0 1.2034 0.8294 7.8813 3.4433 4.2974 6.9231 2.9301 8.0038 3.4231 6.1903 2.8199

8 2.8836 0.9155 0.7775 1.3111 0.9025 2.8271 1.2034 0 0.8796 7.1276 2.7115 3.1676 5.7300 2.0364 7.2455 2.2491 4.9904 2.0579

9 3.1286 0.8748 0.5699 1.5514 0.8777 3.0443 0.8294 0.8796 07.3492 2.7663 3.7328 6.4338 2.5272 7.4234 2.9315 5.7061 2.1347

104.8374 7.1452 7.3764 6.3835 7.4384 4.6922 7.8813 7.1276 7.34920 5.1007 4.9358 4.2166 5.8919 0.8869 5.3750 3.9531 5.9221

11 1.1268 2.2211 2.8485 2.3156 3.0608 0.9045 3.4433 2.7115 2.7663 5.1007 0 1.8544 4.5788 2.2423 4.9970 1.5414 3.8230 1.7300

121.7501 3.7787 3.6503 3.0889 4.0441 1.5982 4.2974 3.1676 3.7328 4.9358 1.8544 0 3.3527 3.0613 4.9231 1.8555 2.5260 1.9664

134.1207 6.5029 6.4038 5.5681 6.5157 4.0534 6.9231 5.7300 6.4338 4.2166 4.5788 3.3527 0 4.6408 4.4928 4.0566 3.1402 4.5774

141.9475 2.8895 2.7290 1.8293 2.4781 2.0226 2.9301 2.0364 2.5272 5.8919 2.2423 3.0613 4.6408 0 6.0952 1.6531 4.0130 2.0245

154.7728 7.0592 7.4651 6.5477 7.5707 4.6101 8.0038 7.2455 7.4234 0.8869 4.9970 4.9231 4.4928 6.0952 0 5.5506 4.1029 5.8931

161.2088 3.0610 2.9318 2.0869 3.0329 1.2382 3.4231 2.2491 2.9315 5.3750 1.5414 1.8555 4.0566 1.6531 5.5506 0 2.8359 1.7943

173.3849 5.7533 5.6631 4.8392 5.7923 3.2996 6.1903 4.9904 5.7061 3.9531 3.8230 2.5260 3.1402 4.0130 4.1029 2.8359 0 3.8305

182.0807 2.4759 2.3055 1.8396 2.5825 1.9540 2.8199 2.0579 2.1347 5.9221 1.7300 1.9664 4.5774 2.0245 5.8931 1.7943 3.8305 0

authentication9
Authentication
  • MDS
  • Distance3D: Without BP
    • True Paintings

0.2428

0.1589

0.1482

0.2285

0.2064

0.2163

0.1422

0.0441

0.2737

    • Imitation Paintings

0.7019

0.3713

0.6394

0.8643

0.5679

0.6853

0.2347

0.4119

0.7159

  • Distance3D : With Block Process
    • True Paintings

0.2350

0.2426

0.0883

0.1471

0.1942

0.2460

0.1552

0.2014

0.0729

    • Imitation Paintings

0.7421

0.3266

0.5909

0.8896

0.4663

0.7425

0.3506

0.7251

0.2686

authentication10
Authentication
  • Without Block Processing
authentication11
Authentication
  • With Block Processing
outline12
Outline
  • Authentication
    • Author Identification
      • Vangogh
  • Style Classification
    • Light
    • Line
    • Color
    • Texture
      • Impressionism
      • Fauvism
      • Cubism
  • Discussion Experiment Result
  • References
style classification light
Style Classification: Light
  • Six different light features
    • P1: Percentage of dark colors
    • P2: Gradient coefficient
    • P3: Standard Deviation of Mean
style classification light cont
Style Classification: Light (cont.)
  • Six different light features
    • P4: Number of local and global maxima in luminance histogram
    • P5: Peak point of luminance histogram correspond
    • P6: Skew value
style classification light cont15
Style Classification: Light (cont.)

Painting style V.S. grayscale histogram

Fauvism

Cubism

Impressionism

outline16
Outline
  • Authentication
    • Author Identification
      • Vangogh
  • Style Classification
    • Light
    • Line
    • Color
    • Texture
      • Impressionism
      • Fauvism
      • Cubism
  • Discussion Experiment Result
  • References
style classification line
Style Classification: Line
  • Number of lines
    • Do the edge detection
    • Added up the number of lines that were 8 pixels in length or longer across the edge.
    • Get the number (number of line).
style classification line cont
Style Classification: Line (cont.)

Impressionism=0.0460

Fauvism=0.0032

Cubism=0.0996

style classification line cont19
Style Classification: Line (cont.)
  • Experiment result

Use Sobel Filter, Threshold=.25

outline20
Outline
  • Authentication
    • Author Identification
      • Vangogh
  • Style Classification
    • Light
    • Line
    • Color
    • Texture
      • Impressionism
      • Fauvism
      • Cubism
  • Discussion Experiment Result
  • References
style classification color
Style Classification: Color
  • RGBXY
    • Characterize the spatial distribution of colors
    • Paintings with larger palette scopes and larger variations in spatial color distribution will have larger singular values
  • HS histogram
    • Number of colors
    • Divided into six colors bins (red, yellow, green, cyan, blue, and magenta),
style classification color cont
Style Classification: Color (cont.)

Impressionism

Fauvism

Cubism

outline24
Outline
  • Authentication
    • Author Identification
      • Vangogh
  • Style Classification
    • Light
    • Line
    • Color
    • Texture
      • Impressionism
      • Fauvism
      • Cubism
  • Discussion Experiment Result
  • References
style classification texture
Style Classification: Texture
  • Why using Gabor Filter?

Cubism Impressionism Fauvism

style classification texture26
Style Classification: Texture
  • Gabor Filter & Feature Vectors
style classification28
Style Classification
  • Any better approach to improve the accuracy?
  • W1, W2, and W3 are the weighting values
discuss experiment result
Discuss Experiment Result
  • Resolution Problems
  • Image Sizes
  • How to solve the different styles in the sphere boundary?
references
References
  • [1] S. Lyu, D. Rockmore and H. Farid, “A digital technique for art authentication,” PNAS, Dec. 2004
  • [2] Robert W. B., and Eero P. S., “ Image compression via joint statistical characterization in the wavelet domain,” IEEE Trans. on Image Processing, Vol. 8, No. 12, Dec. 1999
  • [3] Siwei Lyu and Hany Farid, “Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines,” 5th International Workshop on Information Hiding, Noordwijkerhout.
  • [4] B. S. Manjunath and W. Y. Ma, “Texture Features for Browsing and Retrieval of Image Data,” IEEE Trans on Pattern Analysis Machine Intelligence, Vol. 18, NO. 8, August 1996.
  • [5] Anil K. Jain and Farshid Farrokhnia, “ Unsupervised Texture Segmentation Using Gabor Filters,” IEEE 1990.
  • [6] Daniel P. H., Gregory A. K., and William J. R., “Comparing Images Using the Hausdorff Distance,” IEEE Trans on Pattern Analysis and Machine Intelligence, Vol. 15, No. 9, Sep. 1993
  • [7] Thomas Lombardi, “The Classification of Style in Fine-Art Painting,” CSIS, Pace University, May. 2005
  • [8] Oguz Icoglu, Bilge Gunsel, and Sanem Sariel, “Classification and Indexing of Paintings Based on Art Movement” , Multimedia Signal Processing and Pattern Recognition Lab.
  • [9 ] Florin Cutzu, Riad Hammoud, Alex Leykin, “Estimating the photorealism of images: Distinguishing paintings from photographs”, Department of Computer Science, Indiana University.
  • [10] Greg Pass Ramin ZabihJustin Miller, “Comparing Images Using Color Coherence Vectors”, Computer Science Department Cornell University
  • [11] N.poich. The Web Museum. http://www.ibiblio.org/wm/paint/
  • [12] The Museum of Modern Art. http://www.moma.org
  • [13] The Metropolitan Museum of Art. http://www.metmuseum.org
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