Abstract
Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longer operates in the image space but in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discussed and justified. The experimental results led on the GREC2003 database show that the proposed method is characterized by a good discrimination power, a real robustness to noise with an acceptable time computing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Fifth IAPR International Workshop on Graphics Recognition. Computer Vision Center, Barcelona, Catalonia, Spain, July 30-31 (2003)
Ahmed, N., Natarajan, T., Rao, K.: On image processing and a discrete cosine transform. IEEE Transactions on Computers C-23(1), 90–93 (1974)
Chen, W., Pratt, K.: Scene adaptative coder. IEEE Transactions on Communications COM-32, 225–232 (1984)
Egmont-Petersen, M., de Ridder, D., Handels, H.: Image processing with neural networks-a review. Pattern Recognition 35, 2279–2301 (2002)
Franco, P., Ogier, J.-M., Loonis, P., Mullot, R.: A topological measure for image object recognition. In: Lladós, J., Kwon, Y.-B. (eds.) GREC 2003. LNCS, vol. 3088, pp. 279–290. Springer, Heidelberg (2004)
Franco, P., Ogier, J.-M., Loonis, P., Mullot, R.: Template matching by minimum spanning trees. In: 5th IAPR International Conference on Graphics Recognition (GREC 2003), Barcelone, Spain, pp. 341–352 (2003)
Gersho, A., Gray, R.M.: Vector Quantization and Signal Compression. Kluwer Academic Publishers, Boston (1992) (6 edn., 1999)
Guichard, J., Nasse, D.: Traitement des images numériques pour la réduction du débit binaire. Le Traitement du Signal - Actes des Forums de France Télécom Recherche (2), 1–15 (1994)
Guillas, S., Bertet, K., Ogier, J.M.: Towards an iterative classification based on concept lattice. In: Yahia, S.B., Nguifo, E.M., Belohlavek, R. (eds.) CLA 2006. LNCS (LNAI), vol. 4923, pp. 256–262. Springer, Heidelberg (2008)
Hero, A., Michel, O.: Robust estimation of point process intensity features using k-minimal spanning trees. In: IEEE International Symposium on Information Theory, Germany, June 1997, p. 74 (1997)
Hero, A., Michel, O.: Robust entropy estimation strategies based on edge weighted random graphs. In: SPIE, International Symposium on Optical Science, Engineering and Instrumentation, San Diego (July 1998)
Hero, A., Michel, O.: Asymptotic theory of greedy approximations to minimal k-point random graphs. IEEE Transactions on Information Theory IT 45, 1921–1939 (1921)
Karger, D., Klein, P., Tarjan, R.: A randomized linear-time algorithm to find minimum spanning trees. Journal of the Association for Computing Machinery (ACM) 42(2), 321–328 (1995)
Khotanzad, A., Hong, Y.H.: Rotation invariant image recognition using features selected via a systematic method. Pattern Recognition (23), 1089–1101 (1990)
Kresch, R., Malah, D.: Morphological reduction of skeleton redundancy. Signal Processing 38, 143–151 (1994)
Lladós, J., Valveny, E., Sánchez, G., Martí, E.: Symbol recognition: Current advances and perspectives. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, pp. 104–128. Springer, Heidelberg (2002)
Loeffler, C., Ligtenberg, A., Moschytz, G.: Practical fast 1-d dct algorithms with 11 multiplications. In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP 1989), pp. 988–991 (1989)
Mallat, S.G.: Theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on PAMI 11(7), 674–693 (1989)
Maragos, P., Shafer, R.: Morphological skeleton representations and coding of binary images. IEEE Transactions on Accoustics, Speach and Signal Processing 34(5), 1228–1244 (1986)
Marchand-Maillet, S., Sharaiha, Y.M.: A minimum spanning tree approach to line image analysis. In: Proceedings of the 13th International Conference on Pattern Recognition, August 1996, vol. 2, pp. 225–230 (1996)
Oh, C., Ryu, Y.K.: Study on the center of rotation method based on minimum spanning tree matching for fingerprint recognition. Optical Engineering 43(4), 822–829 (2004)
Osowski, S., Dinh Nghia, D.: Fourier and wavelet descriptors for shape recognition using neural networks-a comparative study. Pattern Recognition 35, 1949–1957 (2002)
Pei, S., Lin, C.: Normalisation of rotationally symmetric shapes for pattern recognition. Pattern Recognition (25), 913–920 (1992)
Pennebaker, W.B., Mitchell, J.L.: The JPEG Still Image Data Compression Standard. Van Nostrand Reinhold, New York (1993)
Rao, K., Yip, P.: Discrete Cosine Transforms - Algorithms, Advantages, Applications. Academic Press, Boston (1990)
Redmond, C., Yukich, J.E.: Limit theorems and rates of convergence for euclidean functionals. Annals of Applied Probability 4(4), 1057–1073 (1994)
Rény, A.: On measures of entropy and information. In: Symposium on Mathematics Statistics and Probabilities, Berkeley, pp. 547–561 (1961)
Serra, J.: Image analysis and mathematical morphology. Theoretical Advances, vol. 2. Academic Press, London (1988)
Soss, M.: On the size of the sphere on influence graph. PhD thesis, Mc Gill University Scholl of Computer Science Montreal (1998)
Tabbone, S., Wendling, L.: Recognition of symbols in grey level line drawings from an adaptation of the radon transform. In: The 17th International Conference on Pattern Recognition, Cambridge, UK, pp. 570–573 (2004)
Tombre, K., Lamiroy, B.: Graphics recognition - from re-engineering to retrieval. In: 7th International Conference on Document Analysis and Recognition (ICDAR 2003), pp. 148–156. IEEE Computer Society, Los Alamitos (2003)
Tombre, K.: Graphics recognition: The last ten years and the next ten years. In: Liu, W., Lladós, J. (eds.) GREC 2005. LNCS, vol. 3926, pp. 422–426. Springer, Heidelberg (2006)
Toussaint, G.: The relative neighborhood graph of a finite planar set. Pattern Recognition, 261–268 (1980)
Vetterli, M., Kovacevic, J.: Wavelets and Subband Coding. Prentice Hall, Englewood Cliffs (1995)
Wallace, G.: The jpeg still picture compression standard. Communications of the Association for Computing Machinery 34(4), 30–44 (1991)
Xu, Y., Olman, V., Xu, D.: Minimum spanning trees for gene expression data clustering. Genome Informatics (12), 24–33 (2001)
Ying, X., Uberbacher, E.C.: 2d image segmentation using minimum spanning trees. Image and Vision Computing 15(1), 47–57 (1997)
Zahn, C.: Graph-theoretical method for detecting and describing gestalt clusters. IEEE Trans. on Computers, 68–86 (1971)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Franco, P., Ogier, JM., Loonis, P., Mullot, R. (2010). A New Minimum Trees-Based Approach for Shape Matching with Improved Time Computing: Application to Graphical Symbols Recognition. In: Ogier, JM., Liu, W., Lladós, J. (eds) Graphics Recognition. Achievements, Challenges, and Evolution. GREC 2009. Lecture Notes in Computer Science, vol 6020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13728-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-13728-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13727-3
Online ISBN: 978-3-642-13728-0
eBook Packages: Computer ScienceComputer Science (R0)