Abstract
We propose a GPU-based algorithm for texture analysis and synthesis of nearly-regular patterns, in our case scanned textiles or similar manufactured surfaces. The method takes advantage of the highly parallel execution on the GPU to generate correlation maps from captured template images. In an analysis step a lattice encoding the periodicity of the texture is computed. This lattice is used to synthesize the smallest texture tile describing the underlying pattern. Compared to other approaches, our method analyzes and synthesizes a valid lattice model without any user interaction. It is robust against small distortions and fast compared to other, more general approaches.
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References
Lindeberg, T.: Scale-space theory: A basic tool for analysing structures at different scales. Journal of Applied Statistics, 224–270 (1994)
Lowe, D.G.: Object recognition from local scale-invariant features. In: International Conference on Computer Vision, pp. 1150–1157 (1999)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)
Morel, J.M., Yu, G.: On the consistency of the SIFT Method. CMLA 26 (2008) (preprint)
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from. In: British Machine Vision Conference, pp. 384–393 (2002)
Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded Up Robust Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Kiryati, N., Gofman, Y.: Detecting symmetry in grey level images: The global optimization approach. In: Proceedings of the 13th International Conference on Pattern Recognition, vol. I, pp. 951–956 (1996)
Scognamillo, R., Rhodes, G., Morrone, C., Burr, D.: A feature-based model of symmetry detection. In: Proceedings Biological Sciences the Royal Society, vol. 270, pp. 1727–1733 (2003)
Loy, G., Eklundh, J.-O.: Detecting Symmetry and Symmetric Constellations of Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 508–521. Springer, Heidelberg (2006)
Lin, H.C., Wang, L.L., Yang, S.N.: Extracting periodicity of a regular texture based on autocorrelation functions. Pattern Recogn. Lett. 18, 433–443 (1997)
Hays, J., Leordeanu, M., Efros, A.A., Liu, Y.: Discovering Texture Regularity as a Higher-Order Correspondence Problem. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 522–535. Springer, Heidelberg (2006)
Lin, W.-C., Liu, Y.: Tracking Dynamic Near-Regular Texture Under Occlusion and Rapid Movements. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 44–55. Springer, Heidelberg (2006)
Park, M., Collins, R.T., Liu, Y.: Deformed Lattice Discovery Via Efficient Mean-Shift Belief Propagation. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 474–485. Springer, Heidelberg (2008)
Dischler, J.M., Zara, F.: Real-time structured texture synthesis and editing using image-mesh analogies. The Visual Computer 22, 926–935 (2006)
Liu, Y., Liu, a.Y., Tsin, Y.: The promise and the perils of near-regular texture. International Journal of Computer Vision 62, 1–2 (2002)
Liu, Y., Collins, R.T., Tsin, Y.: A computational model for periodic pattern perception based on frieze and wallpaper groups. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 354–371 (2004)
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Eibner, G., Fuhrmann, A., Purgathofer, W. (2012). GPU-Based Multi-resolution Image Analysis for Synthesis of Tileable Textures. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_47
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DOI: https://doi.org/10.1007/978-3-642-33191-6_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33190-9
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