Abstract
Dongba hieroglyph is a kind of very primitive picture hieroglyphs. Its picture features allow us to analyse the overall and local features of Dongba characters in combination with the existing feature extraction, simplification and segmentation algorithms for shape in computer vision. Moreover, the analysis of the local features of Dongba hieroglyphs play an important role in the study of Dongba hieroglyph’s writing, the evolution process of hieroglyphs and the comparison between similar hieroglyphs. Therefore, in this paper, we first use the Chain-Code Based Connected Domain Priority Marking Algorithm (CDPM) and the Discrete Curve Evolution Algorithm (DCE) to obtain the simplified feature curve of Dongba hieroglyph. Then, we focus on the selection and adjustment of demarcation points and local curve segmentation. And, the experiment proves that our method can further correct the potential errors in the curve segmentation, which is helpful to improve the correct rate of hieroglyph’s local feature extraction.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
He, L.M.: The research of Dongba culture heritage. Social Sciences in Yunnan (1), pp. 83–87 (2004)
Rock, J.F., Khi, N.: English encclopedic dictionary (Part I). Roma Istituto Italiano Peril Medio ed Estreme Prientale, Roma (1963)
Fang, G.Y., He, Z.W.: The Dictionary of Naxi Hieroglyphic. Yunnan People’s Publishing House, Kunming (2005)
Li, L.C.: Pronunciation Dictionary of Naxi Hieroglyphic. Yunnan Nationalities Publishing House, Kunming (2001)
Guo, H., Zhao, J.Y.: Segmentation method for NaXi pictograph character recognition. J. Convergence Inf. Technol. 5(6), 87–98 (2010)
Guo, H., Zhao, J.Y.: Research on feature extraction for character recognition of Naxi pictograph. J. Comput. 6(5), 947–954 (2011)
Guo, H., Yin, J.H., Zhao, J.Y.: Feature dimension reduction of naxi pictograph recognition based on LDA. Int. J. Comput. Sci. 9(1), 90–96 (2012)
Zhu, Q., Wang, X., Keogh, E., Lee, S.H.: Augmenting the generalized hough transform to enable the mining of petroglyphs. In: Proceeding of ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1057–1066 (2009)
Zhu, Q., Wang, X., Keogh, E., Lee, S.H.: An efficient and effective similarity measure to enable data mining of petroglyphs. Data Min. Knowl. Disc. 23(1), 91–127 (2011)
Zhou, Y., Liu, J.T., Bai, X.: Research and perspective on shape matching. Acta Automatica Sin. 38(6), 889–910 (2012)
Yang, Y.T., Kang, H.L.: A novel algorithm of contour tracking and partition for Dongba hieroglyph. In: Processing of 13th Chinese Conference IGTA 2018, pp. 453–463 (2018)
Latecki, L.J., LakaÈmper, R.: Polygon evolution by vertex deletion. In: Processing in International Conference of Scale-Space Theories in Computer Vision, pp. 398–409 (1999)
Latecki, L.J., LakaÈmper, R.: Convexity rule for shape decomposition based on discrete contour evolution. Comput. Vis. Image Underst. 73(3), 441–454 (1999)
Latecki, L.J., LakaÈmper, R.: Shape similarity measure based on correspondence of visual parts. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1–6 (2000)
Chen, B.F., Qian, Z.F.: An algorithm for identifying convexity-concavity of a simple polygon. J. Comput. Aided Des. Comput. Graph. 2(14), 214–217 (2002)
Song, X.M., Cheng, C.X.: An Analysis and Investigation of Algorithms for Identifying Convexity-Concavity of a Simple Polygon. Remote Sens. Land Resour. 9(13), 25–30 (2011)
Acknowledgements
This research was partially supported by the Scientific Research Fund of Yunnan Education Department (2018JS748).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Yang, Y., Kang, H. (2020). Adjustment and Correction Demarcation Points in Dongba Hieroglyphic Feature Curves Segmentation. In: Liu, Q., Mısır, M., Wang, X., Liu, W. (eds) The 8th International Conference on Computer Engineering and Networks (CENet2018). CENet2018 2018. Advances in Intelligent Systems and Computing, vol 905. Springer, Cham. https://doi.org/10.1007/978-3-030-14680-1_55
Download citation
DOI: https://doi.org/10.1007/978-3-030-14680-1_55
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14679-5
Online ISBN: 978-3-030-14680-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)