Abstract
We propose a novel statistical descriptor, Multiple References Histogram Matrix (MRHM), for robust shape retrieval, especially for degraded shape images. For each shape image, MRHM first generates uniform grids and filters noises in each grid by line Hough transformations and curve-fitting transformations. Then MRHM selects a reference for each grid and calculates its local distribution between the reference point and the shape pixels. Finally, all the local distributions are integrated into a global distribution matrix for matching symbols. Experimental results on the MPEG-7 Shape Silhouette Database and the GREC2005 Shape Database show that the proposed method’s recognition rate for degraded shape images is greatly improved over a recent method (SFHM).
This is a preview of subscription content, log in via an institution to check access.
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
Huang, X., Gu, J., Wu, Y.: A Constraint Approach to Multifont Chinese Character Recognition. IEEE TPAMI 15, 838–843 (1993)
Ah-Soon, C., Tombre, K.: Architectural Symbol Recognition Using a Network of Constraints. Pattern Recognition Letters 22(2), 231–248 (2001)
Valveny, E., Matri, E.: A Model for Image Generation and Symbol Recognition through the Deformation of Linear Shapes. Pattern Recognition Letters 24, 2857–2867 (2003)
Su, Y.: Symbol Recognition via Statistical Integration of Pixel-level Constraint Histograms: A New Descriptor. IEEE TPAMI 27(2), 278–281 (2005)
Belongie, S., Malik, J., Puzhicha, J.: Shape Matching and Object Recognition Using Shape Contexts. IEEE TPAMI 24(4), 509–522 (2002)
Ling, H., Jacobs, D.W.: Shape Classification Using Inner-Distance. IEEE TPAMI 29(2), 286–299 (2007)
Zhang, W., Liu, W.Y., Zhang, K.: Symbol Recognition with Kernel Density Matching. IEEE TPAMI 25(12), 2020–2024 (2006)
Zhang, J., Liu, W.Y.: A Pixel-level Statistical Structural Descriptor for Shape Measure and Recognition. In: ICDAR 2009, Spain, pp. 386–390 (2009)
Xu, C., Liu, J., Tang, X.: 2D Shape Matching by Contour Flexibility. IEEE TPAMI 31(1), 180–186 (2009)
Common, P.: Independent Component Analysis, a New Concept. Signal Processing 36, 287–314 (1994)
Hyvärinen, A., Oja, E.: Independent Component Analysis: Algorithms and Application. Neural Networks 13(4-5), 411–430 (2000)
Song, J.Q., Su, F., et al.: Line net global vectorization: an algorithm and its performance evaluation. In: CVPR 2000, vol. (2), pp. 383–388 (2000)
http://www.imageprocessingplace.com/root_files_V3/image_databases.htm
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
Wang, T., Lu, T., Liu, W. (2010). Robust Shape Retrieval through a Novel Statistical Descriptor. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_30
Download citation
DOI: https://doi.org/10.1007/978-3-642-15702-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15701-1
Online ISBN: 978-3-642-15702-8
eBook Packages: Computer ScienceComputer Science (R0)