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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 l.jpg

Art Authentication &Painting Style Classification

Wan-Ting Lee

Chin-Sheng Chen

5/10/2006 Multimedia Security Systems


Outline l.jpg

Outline

  • Authentication

    • Author Identification

      • Van Gogh

  • Style Classification

    • Light

    • Line

    • Color

    • Texture

      • Impressionism

      • Fauvism

      • Cubism

  • Discuss Experiment Result

  • References


Authentication l.jpg

Authentication

  • Paintings


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Authentication

  • Architecture


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Authentication

  • DWT


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Authentication

  • Feature Vectors


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Authentication

  • Feature Vectors


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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


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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


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Authentication

  • Without Block Processing


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Authentication

  • With Block Processing


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Outline

  • Authentication

    • Author Identification

      • Vangogh

  • Style Classification

    • Light

    • Line

    • Color

    • Texture

      • Impressionism

      • Fauvism

      • Cubism

  • Discussion Experiment Result

  • References


Style classification light l.jpg

Style Classification: Light

  • Six different light features

    • P1: Percentage of dark colors

    • P2: Gradient coefficient

    • P3: Standard Deviation of Mean


Style classification light cont l.jpg

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


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Style Classification: Light (cont.)

Painting style V.S. grayscale histogram

Fauvism

Cubism

Impressionism


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Outline

  • Authentication

    • Author Identification

      • Vangogh

  • Style Classification

    • Light

    • Line

    • Color

    • Texture

      • Impressionism

      • Fauvism

      • Cubism

  • Discussion Experiment Result

  • References


Style classification line l.jpg

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 l.jpg

Style Classification: Line (cont.)

Impressionism=0.0460

Fauvism=0.0032

Cubism=0.0996


Style classification line cont19 l.jpg

Style Classification: Line (cont.)

  • Experiment result

Use Sobel Filter, Threshold=.25


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Outline

  • Authentication

    • Author Identification

      • Vangogh

  • Style Classification

    • Light

    • Line

    • Color

    • Texture

      • Impressionism

      • Fauvism

      • Cubism

  • Discussion Experiment Result

  • References


Style classification color l.jpg

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 l.jpg

Style Classification: Color (cont.)

Impressionism

Fauvism

Cubism


Style classification l.jpg

Style Classification


Outline24 l.jpg

Outline

  • Authentication

    • Author Identification

      • Vangogh

  • Style Classification

    • Light

    • Line

    • Color

    • Texture

      • Impressionism

      • Fauvism

      • Cubism

  • Discussion Experiment Result

  • References


Style classification texture l.jpg

Style Classification: Texture

  • Why using Gabor Filter?

Cubism Impressionism Fauvism


Style classification texture26 l.jpg

Style Classification: Texture

  • Gabor Filter & Feature Vectors


Style classification texture27 l.jpg

Style Classification: Texture

  • Simulation Result


Style classification28 l.jpg

Style Classification

  • Any better approach to improve the accuracy?

  • W1, W2, and W3 are the weighting values


Style classification29 l.jpg

Improvement Result

Style Classification


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Discuss Experiment Result

  • Resolution Problems

  • Image Sizes

  • How to solve the different styles in the sphere boundary?


References l.jpg

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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