Two Typical Legends Automatic Recognition in Geological Section Map of Metro Project
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There is important information in the geological section map of metro project for construction safety risk identification. Therefore geological section automatic recognition is a core process for risk identification automation, however, legends in the geological section map automatic recognition by computer is a foundation work. This paper proposes the categories of legends, the challenges and probabilities of legends recognition, and presents the methodology and detailed algorithms of legend of “clay” and “silty clay” recognition as example. At last an automatic legends recognition application example on the project of Pangxiejia Station of Wuhan Metro Line 2 is presented and geological stratum information recognition algorithms of the station exterior is proposed.
KeywordsAutomatic legend recognition Geological section map Feature coefficient Metro project
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- 2.T&TI: Collapse in Prague,2010, Tunnels & Tunneling International, Available at www.tunnelsonline.info, accessed 7/12/2010.
- 3.Doermann, D.S.: An introduction to vectorization and segmentation. In: Tombre, K., Chhabra, A. K. (eds.) Graphics Recognition: Algorithms and Systems LNCS 1389, pp 1–8 (1998)Google Scholar
- 4.Liu, W., Dori, D.: A generic integrated line detection algorithm and its object–process specification. Comp. Vision Image Underst. 70 (2), 420–437 (1998)Google Scholar
- 5.Cai, Z., Xu, G.: Artificial Intelligence:Principles and Applications(Third Edition). Tsinghua university Press, Beijing (2003)Google Scholar
- 6.Dori, D.: Vector-based arc segmentation in the machine drawing understanding system environment. IEEE TransPAMI 17 (11), 1057–1068 (1995)Google Scholar
- 7.Dave, E.: An algorithm for arc segmentation in engineering drawing. Lect. Notes Comput. Sci. 23, 347–356 (2002)Google Scholar
- 8.Habed, A., Boufama, B.: Dimension sets detection in technical drawings.In:Proc. IAPR’99, pp 217–223 (1999)Google Scholar
- 10.Ah-Soon, C.: A constraint net work for symbol detection in architectural drawings. Graph. Recog. Algoritm. Syst., 180–90 (1998)Google Scholar
- 11.Yang, R., Jia, H., Yang, C., et al.: A highly-efficient constraint- network-based approach for symbol recognition of engineering drawings. Computer-aided Des. Comput. Graph. 14 (9), 829–834 (2002)Google Scholar
- 13.Zhao, J.: Research on the reconstruction technology of architectural drawings and the extraction method of its model information. J. Hunan Univ. Technol. 23 (3), 4144 (2009)Google Scholar
- 15.Chen, J., Zhou, Z., Chen, G., et al.: Automatic formation method of prospecting line profile map based on drill hole database. J. Cent. South Univer. 36 (2), 487–490 (2005)Google Scholar
- 16.Zhu, Y., Liu, X., Chen, S., et al.: A research on automatic generating software of geologic section based on GIS. J. Nanjing Normal Univ. 30 (3), 104–108 (2007)Google Scholar
- 17.Wang, J., BAO, S., YU, Y., et al.: Realization of geological section map model based GIS template. Sci. Surv. Mapp. 33 (5), 184–186 (2008)Google Scholar
- 18.Tan, Z., Wang, L., Xiong, S., et al.: A new method for automatic generation of complex geological mining engineer profile chart. J. Cent. South Univer. 43 (2), 1092–1097 (2012)Google Scholar
- 19.Beijing urban construction survey and mapping Institute: Code on geotechnical investigation for metro and light rail transit (GB50307-1999)Chinese Plan Press,Beijing (2000)Google Scholar