Abstract
In repeated pattern analysis, peak number detection in autocorrelation is of key importance, which subsequently determines the correctness of the constructed lattice. Previous work inevitably needs users to select peak number manually, which limits its generalization to applications in large image database. The main contribution of this paper is to propose an optimization-based approach for automatic peak number detection, i.e., we first formulate it as an optimization problem by a straightforward yet effective criterion function, and then resort to Simulated Annealing to optimize it. Based on this approach, we design a new feature to depict image symmetry property which can be automatically extracted for repeated pattern retrieval. Experimental results demonstrate the effectiveness of the optimization approach and the superiority of symmetry feature over wavelet feature in discriminating similar repeated patterns.
This work was performed at Microsoft Research Asia.
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References
Gruenbaum, B., Grunbaum, B., Shephard, G.C.: Tilings and Patterns. W.H. Freeman and Company, New York (1987)
Kali: Programs that can automatically generate 2D planar crystallographic patterns, http://www.geom.umn.edu/apps/kali/
Leung, L., Malik, J.: Detecting, localizing and grouping repeated scene elements. In: Buxton, B.F., Cipolla, R. (eds.) ECCV 1996. LNCS, vol. 1064, pp. 546–555. Springer, Heidelberg (1996)
Lin, H., Wang, L., Yang, S.: Extracting periodicity of a regular texture based on autocorrelation functions. Pattern Recognition Letters 18, 433–443 (1997)
Liu, Y., Collins, R.: A computational model for repeated pattern perception using Frieze and Wallpaper groups. In: Proc. CVPR, vol. 1, pp. 537–544 (2000)
Schaffalitzky, F., Zisserman, A.: Geometric grouping of repeated elements within images. In: Proc. BMVC, pp. 13–22 (1998)
Starovoitov, V.V., Jeong, S.Y., Park, R.H.: Texture periodicity detection: Features, properties, and comparisons. IEEE SMC-A 28(6), 839–848 (1998)
Unser, M.: Texture classification and segmentation using wavelet frames. IEEE Trans. on Image Processing 4, 1549–1560 (1995)
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© 2004 Springer-Verlag Berlin Heidelberg
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He, J., Li, M., Zhang, HJ., Tong, H., Zhang, C. (2004). Automatic Peak Number Detection in Image Symmetry Analysis. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30543-9_15
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DOI: https://doi.org/10.1007/978-3-540-30543-9_15
Publisher Name: Springer, Berlin, Heidelberg
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