Abstract
This paper presents an efficient shape matching method based on XML data, we extract the contour of the shape and this one is represented by set of points. Using corner detection method for representing the contour by a sequence of convex and concave segments. After, each segment is described by local and global features, this features are coded in string of symbols and stored in a XML file. Finally, using the dynamic programming, we find the optimal alignment between sequences of symbols. Results are presented and compared with existing methods using MATLAB for KIMIA-25 database and MPEG7 databases.
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Wolfson, H.J.: On Curve Matching. IEEE Trans. on Pattern Analysis and Machine Intelligence 12, 483–489 (1990)
Kishon, E., Hastie, T., Wolfson, H.J.: 3-D Curve Matching using Splines. J. of Robotic Systems 8, 723–743 (1991)
Barequet, G., Sharir, M.: Partial Surface Matching by Using Directed Footprints. In: Symposium on Computational Geometry, pp. C-9–C-10 (1996)
Biederman, I., Ju, G.: Surface versus edge-based determinants of visual recognitions. Cognit. Psychol. 20, 38–64 (1988)
Geiger, D., Gupta, A., Costa, L.A., Vlontzos, J.: Dynamic Programming for Detecting, Tracking amd Matching Deformable contours. IEEE Trans. on Pattern Analysis and Machine Intelligence 17(3), 294–302 (1995)
Floreby, L.: A Multiscale Algorithm for Closed Contour Matching in Image Sequence. In: IEEE Intern. Conf. on Pattern Recognition, pp. 884–888 (1996)
Petrakis, E.G.M., Diplaros, A., Milios, E.: Matching and retrieval of distorted and occluded shapes using dynamic programming. IEEE Trans. Pattern Anal. Mach. Intell. 24(11), 1501–1516 (2002)
Yu, M.H., Lim, C.C., Jin, J.S.: Shape similarity using XML and portal technology. In: Visual Information Processing, VIP, Sydney, Australia (2006)
Fung, G.S.K., Yung, N.H.C., Pang, G.K.H.: Vehicle shape approximation from motion for visual traffic surveillance. In: Proc. IEEE 4th Int. Conf. on Intelligent Transportation Systems, pp. 201–206 (2001)
Manku, G.S., Jain, P., Aggarwal, A., Kumar, A., Banerjee, L.: Object tracking using affine structure for point correspondence. In: Proc. 1997 IEEE Comput. Soc. Conf. on Computer Vision and Pattern Recognition, pp. 704–709 (1997)
Serra, B., Berthod, M.: 3-D model localization using highresolution reconstruction of monocular image sequences. IEEE Trans. Image Process. 6(1), 175–188 (1997)
He, X.C., Yung, N.H.C.: Corner detector based on global and local curvature properties. Optical Engineering 47(5), 057008-1–057008-12 (2008)
Gherabi, N., Bahaj, M.: A new shape descriptor using XML. IJCSE 3, 1369–1376 (2011)
Ristad, E.S., Yianilos, P.N.: Learning string edit distance. IEEE Trans. Pattern Anal. Mach. Intell. 20(5), 522–532 (1998)
Daliri, M.R., Delponte, E., Verri, A., Torre, V.: Shape Categorization Using String Kernels. In: Yeung, D.-Y., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds.) SSPR 2006 and SPR 2006. LNCS, vol. 4109, pp. 297–305. Springer, Heidelberg (2006)
Super, B.J.: Learning chance probability functions for shape retrieval or classification. In: Proceedings of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (June 2004)
Attalla, E., Siy, P.: Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching. Pattern Recognition 38(12) (2005)
Super, B.J.: Retrieval from shape databases using chance probability functions and fixed correspondence. Int. J. Pattern Recognition Artif. Intell. 20(8), 1117–1137 (2006)
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Gherabi, N., Bahaj, M. (2012). Outline Matching of the 2D Shapes Using Extracting XML Data. In: Elmoataz, A., Mammass, D., Lezoray, O., Nouboud, F., Aboutajdine, D. (eds) Image and Signal Processing. ICISP 2012. Lecture Notes in Computer Science, vol 7340. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31254-0_57
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DOI: https://doi.org/10.1007/978-3-642-31254-0_57
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