Abstract
Principal curves are nonlinear generalizations of principal components analysis. They are smooth self-consistent curves that pass through the middle of the distribution. By analysis of existed principal curves, we learn that a soft k-segments algorithm for principal curves exhibits good performance in such situations in which the data sets are concentrated around a highly curved or self-intersecting curves. Extraction of features are critical to improve the recognition rate of off-line handwritten characters. Therefore, we attempt to use the algorithm to extract structural features of off-line handwritten characters. Experiment results show that the algorithm is not only feasible for extraction of structural features of characters, but also exhibits good performance. The proposed method can provide a new approach to the research for extraction of structural features of characters.
This is a preview of subscription content, log in via an institution to check access.
References
Hastie, T.: Principal curves and surfaces. Laboratory for Computational Statistics, Stanford University, Department of Statistics, Technical report 11 (1984)
Banfield, J.D., Raftery, A.E.: Ice floe identification in satellite images using mathematical morphology and clustering about principal curves. J. Am. Stat. Assoc. 87, 7–16 (1992)
Kegl, B., KrzyzaK, A., et al.: A polygonal line algorithm for constructing principal curves. In: Proceedings of Neural Information Processing System, pp. 501–507. Computer Press, Denver Colorado, USA (1999)
Zhang, J.P., Chen, D.W., Kruger, U.: Adaptive constraint k-segment principal curves for intelligent transportation systems. IEEE Trans. Intell. Transp. Syst. 9, 666–677 (2008)
VerbeeK, J.J., Vlassis, N., Krose, B.: A K-segments algorithm for finding principal curves. Technical report: Pattern Recognition Letters 23, Computer Science of Institute, University of Amsterdam, pp. 1009–1017 (2002)
Verbeek, J.J., Vlassis, N., Kröse, B.J.A.: A soft \(k\)-segments algorithm for principal curves. In: Dorffner, G., Bischof, H., Hornik, K. (eds.) ICANN 2001. LNCS, vol. 2130, pp. 450–456. Springer, Heidelberg (2001)
Delicado, P.: Another look at principal curves and surfaces. J. Multivar. Anal. 7, 84–116 (2001)
Zhang, J.P., Wang, J.: An overview of principal curves. Chin. J. Comput. 26, 129–146 (2003)
Bas, E., Erdogmus, D.: Principal curves as skeletons of tubular objects: locally characterizing the structures of axons. Neuroinformatics 9, 181–191 (2011)
Wang, H.N., Lee, T.C.M.: Extraction of curvilinear features from noisy point patterns using principal curves. Pattern Recogn. Lett. 29, 2078–2084 (2008)
Acknowledgements
This paper is supported by the National Social Science Fund (Granted No. 13CFX049), Shanghai University Young Teacher Training Program (Granted No. hdzf10008) and the Research Fund for East China University of Political science and Law (Granted No. 11H2K034).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Jiao, N. (2015). Extraction of Off-Line Handwritten Characters Based on a Soft K-Segments for Principal Curves. In: Yao, Y., Hu, Q., Yu, H., Grzymala-Busse, J.W. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Lecture Notes in Computer Science(), vol 9437. Springer, Cham. https://doi.org/10.1007/978-3-319-25783-9_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-25783-9_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25782-2
Online ISBN: 978-3-319-25783-9
eBook Packages: Computer ScienceComputer Science (R0)