Manga are popular artistic form that have gained worldwide audience. Traditional scan-based digitization cannot properly and efficiently deliver the Manga artwork on electronic displays with different resolutions and screen sizes. Therefore, this research aims to design a pipeline to transform a raster Manga object to a vector representation for resolution independent rendering and interactive manipulation. The Manga object is decomposed into Manga elements including borders and shading regions using the line tracing approach and the cartoon+texture filter. To remove jagged edges, the borders are polished with the curve based Gaussian refiner. After the vectorization process is done, users can lay down scribbles to form of contextual components that can be edited independently from the original object. The final results are generated by rendering the borders with the curve-based shader and the shading regions with procedural texture along with their extracted properties. Our proposed vector representation can be not only magnified infinitely but also manipulated easily to generate interesting results: Deform the Bézier curves and triangle mesh for various animation effects. Users can easily change the pattern types or edit the pattern properties. A virtual light can be added to change the shading.

Manga are popular artistic form that have gained worldwide audience. Traditional scan-based digitization cannot properly and efficiently deliver the Manga artwork on electronic displays with different resolutions and screen sizes. Therefore, this research aims to design a pipeline to transform a raster Manga object to a vector representation for resolution independent rendering and interactive manipulation. The Manga object is decomposed into Manga elements including borders and shading regions using the line tracing approach and the cartoon+texture filter. To remove jagged edges, the borders are polished with the curve based Gaussian refiner. After the vectorization process is done, users can lay down scribbles to form of contextual components that can be edited independently from the original object. The final results are generated by rendering the borders with the curve-based shader and the shading regions with procedural texture along with their extracted properties. Our proposed vector representation can be not only magnified infinitely but also manipulated easily to generate interesting results: Deform the Bézier curves and triangle mesh for various animation effects. Users can easily change the pattern types or edit the pattern properties. A virtual light can be added to change the shading.

[1] J. Kopf and D. Lischinski, “Digital reconstruction of halftoned color comics,” ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2012), vol. 31, p. to appear, Nov. 2012.
[2] G. Noris, A. Hornung, R. W. Sumner, M. Simmons, and M. Gross, “Topology- driven vectorization of clean line drawings,” ACM Trans. Graph., vol. 32, pp. 4:1–4:11, Feb. 2013.
[3] Y. Qu, T.-T. Wong, and P.-A. Heng, “Manga colorization,” ACM Transactions on Graphics (SIGGRAPH 2006 issue), vol. 25, pp. 1214–1220, July 2006.
[4] Y. Qu, W.-M. Pang, T.-T. Wong, and P.-A. Heng, “Richness-preserving manga screening,” ACM Transactions on Graphics (SIGGRAPH Asia 2008 issue), vol. 27, pp. 155:1–155:8, December 2008.
[5] S.-H. Zhang, T. Chen, Y.-F. Zhang, S.-M. Hu, and R. Martin, “Vectorizing car- toon animations,” Visualization and Computer Graphics, IEEE Transactions on, vol. 15, pp. 618–629, July 2009.
[6] M. Galun, E. Sharon, R. Basri, and A. Brandt, “Texture segmentation by multiscale aggregation of filter responses and shape elements,” in Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2, ICCV ’03, pp. 716–, 2003.
[7] M. Varma and A. Zisserman, “Texture classification: are filter banks neces- sary?,” in Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on, vol. 2, pp. II–691–8 vol.2, June 2003.
[8] T. Hofmann, J. Puzicha, and J. Buhmann, “Unsupervised texture segmenta- tion in a deterministic annealing framework,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 20, pp. 803–818, Aug 1998.
[9] N. Paragios and R. Deriche, “Geodesic active regions for supervised texture segmentation,” in Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on, vol. 2, pp. 926–932 vol.2, 1999.
[10] Z. Liao, H. Hoppe, D. Forsyth, and Y. Yu, “A subdivision-based representation for vector image editing,” IEEE Transactions on Visualization and Computer Graphics, vol. 99, no. PrePrints, 2012.
[11] M. Finch, J. Snyder, and H. Hoppe, “Freeform vector graphics with controlled thin-plate splines,” ACM Trans. Graph., vol. 30, no. 6, pp. 166:1–166:10, 2011.
[12] Y.-K. Lai, S.-M. Hu, and R. R. Martin, “Automatic and topology-preserving gradient mesh generation for image vectorization,” ACM Trans. Graph., vol. 28, no. 3, pp. 85:1–85:8, 2009.
[13] T. Xia, B. Liao, and Y. Yu, “Patch-based image vectorization with automatic curvilinear feature alignment,” ACM Trans. Graph., vol. 28, no. 5, pp. 115:1– 115:10, 2009.
[14] S. Battiato and F. Stanco, “A new descreening technique in the frequency domain.,” in Eurographics Italian Chapter Conference, pp. 137–142, 2006.
[15] C. J. Stanger, T. Tran, and E. H. Barney Smith, “Descreening of color halftone images in the frequency domain,” 2011.
[16] Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, “Edge-preserving decom- positions for multi-scale tone and detail manipulation,” ACM Trans. Graph., vol. 27, no. 3, pp. 67:1–67:10, 2008.
[17] K. Subr, C. Soler, and F. Durand, “Edge-preserving multiscale image decompo- sition based on local extrema,” ACM Trans. Graph., vol. 28, no. 5, pp. 147:1– 147:9, 2009.
[18] H. Siddiqui and C. A. Bouman, “Training-based descreening,” Trans. Img. Proc., vol. 16, no. 3, pp. 789–802, 2007.
[19] R. L. Stevenson IEEE Transactions on Image Processing, vol. 6, pp. 574–583, 1997.
[20] C. Loop and J. Blinn, “Resolution independent curve rendering using pro- grammable graphics hardware,” ACM Trans. Graph., vol. 24, pp. 1000–1009, July 2005.
[21] A. Jacobson, I. Baran, J. Popovi´c, and O. Sorkine, “Bounded biharmonic weights for real-time deformation,” ACM Transactions on Graphics (proceed- ings of ACM SIGGRAPH), vol. 30, no. 4, pp. 78:1–78:8, 2011.
[22] P. Selinger, “Potrace: a polygon-based tracing algorithm,” 2003.
[23] T. Ojala, M. Pietik¨ainen, and D. Harwood, “A comparative study of texture measures with classification based on featured distributions,” Pattern Recogni- tion, vol. 29, no. 1, pp. 51–59, 1996.
[24] M. Yvinec, “2D triangulations,” in CGAL User and Reference Manual, CGAL Editorial Board, 4.3 ed., 2013.
[25] L. Rineau, “2D conforming triangulations and meshes,” in CGAL User and Reference Manual, CGAL Editorial Board, 4.3 ed., 2013.
[26] H. Liu, W. Liu, and L. Latecki, “Convex shape decomposition,” in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, pp. 97– 104, June 2010.
[27] Y. Zheng and D. Doermann, “Robust point matching for nonrigid shapes by preserving local neighborhood structures,” Pattern Analysis and Machine In- telligence, IEEE Transactions on, vol. 28, pp. 643–649, April 2006.
[28] S. Gustavson, “Procedural textures in glsl,” in OpenGL Insights (P. Cozzi and C. Riccio, eds.), pp. 105–120, CRC Press, 2012.
[29] A. Buades, T. Le, J. M. Morel, and L. Vese, “Fast cartoon + texture image filters,” Image Processing, IEEE Transactions on, vol. 19, pp. 1978–1986, Aug 2010.
[30] L. Demaret, N. Dyn, and A. Iske, “Image compression by linear splines over adaptive triangulations,” in Signal Processing, pp. 1604–1616, 2006.
[31] T. Igarashi, T. Moscovich, and J. F. Hughes, “As-rigid-as-possible shape manip- ulation,” in ACM SIGGRAPH 2005 Papers, SIGGRAPH ’05, pp. 1134–1141, 2005.
[32] K. Itoh and Y. Ohno, “A curve fitting algorithm for character fonts.,” Electronic Publishing, vol. 6, no. 3, pp. 195–205, 1993.
[33] S. Jeschke, D. Cline, and P. Wonka, “Estimating color and texture parameters for vector graphics,” Computer Graphics Forum, vol. 30, pp. 523–532, Apr. 2011.
[34] G. Lecot and B. Levy, “Ardeco: Automatic region detection and conversion,” in Eurographics Symposium on Rendering, 2006.
[35] Y. Li, J. Sun, C.-K. Tang, and H.-Y. Shum, “Lazy snapping,” ACM Trans. Graph., vol. 23, pp. 303–308, Aug. 2004.
[36] J. ming Lien and N. M. Amato, “Approximate convex decomposition of poly- gons,” in In Proc. 20th Annual ACM Symp. Computat. Geom. (SoCG, pp. 17– 26, 2004.
[37] F. Mai, C. Q. Chang, and Y. Hung, “Affine-invariant shape matching and recognition under partial occlusion,” in Image Processing (ICIP), 2010 17th IEEE International Conference on, pp. 4605–4608, Sept 2010.
[38] B. S. Manjunath and W. Ma, “Texture features for browsing and retrieval of image data,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI - Special issue on Digital Libraries), vol. 18, pp. 837–42, Aug 1996.
[39] I. McEwan, D. Sheets, S. Gustavson, and M. Richardson, “Efficient computa- tional noise in glsl,” CoRR, vol. abs/1204.1461, 2012.
[40] T. Ojala, M. Pietikainen, and D. Harwood, “Performance evaluation of texture measures with classification based on kullback discrimination of distributions,” in Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision amp; Image Processing., Proceedings of the 12th IAPR International Conference on, vol. 1, pp. 582–585 vol.1, Oct 1994.
[41] A. Orzan, A. Bousseau, H. Winnem¨oller, P. Barla, J. Thollot, and D. Salesin, “Diffusion curves: a vector representation for smooth-shaded images,” ACM Trans. Graph., vol. 27, no. 3, pp. 92:1–92:8, 2008.
[42] S. Osher and J. A. Sethian, “Fronts propagating with curvature-dependent speed: Algorithms based on hamilton-jacobi formulations,” Journal of Compu- tational Physics, vol. 79, no. 1, pp. 12 – 49, 1988.
[43] C. Rother, V. Kolmogorov, and A. Blake, “”grabcut”: Interactive foreground extraction using iterated graph cuts,” ACM Trans. Graph., vol. 23, pp. 309–314, Aug. 2004.
[44] D. Sy´kora, J. Buri´anek, and J. Zˇa´ra, “Sketching cartoons by example,” in Pro- ceedings of Eurographics Workshop on Sketch-Based Interfaces and Modeling, pp. 27–34, 2005.
[45] J. Sethian, Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge Monographs on Applied and Computational Mathematics, Cambridge University Press, 1999.
[46] J. Sun, L. Liang, F. Wen, and H.-Y. Shum, “Image vectorization using opti- mized gradient meshes,” ACM Trans. Graph., vol. 26, no. 3, 2007.
[47] S. Swaminarayan and L. Prasad, “Rapid automated polygonal image decom- position,” in Applied Imagery and Pattern Recognition Workshop, 2006. AIPR 2006. 35th IEEE, p. 28, oct. 2006.
[48] R. Wein, E. Berberich, E. Fogel, D. Halperin, M. Hemmer, O. Salzman, and B. Zukerman, “2D arrangements,” in CGAL User and Reference Manual, CGAL Editorial Board, 4.4 ed., 2000.
[49] T. P. Weldon, W. E. Higgins, and D. F. Dunn, “Efficient gabor filter design for texture segmentation,” Pattern Recognition, vol. 29, no. 12, pp. 2005 – 2015, 1996.
[50] F. E. Williams, The DC Comics Guide to Digitally Drawing Comics. New York, NY, USA: Watson-Guptill Publications, Inc., 2009.