Abstract
A stable skeleton is very important to some applications such as vehicle navigation, object represent and pattern recognition. The connection skeleton is just one that not only can be computed stably but also can figure the connectivity structure of contour. A new method named continuous connectivity detection and a new model named approximate regular polygon (ARP) were proposed for connection skeleton extraction. Both the method and the model were tested by the real maps of road network including flyovers, interchanges and other common object contours. Satisfactory results were obtained.
Similar content being viewed by others
References
Pavlidis T. A review of algorithms for shape analysis [J]. Computer Graphics and Image Processing, 1978, 7: 243–258.
Blum H. A transformation for extracting new descriptors[C]//Symp Models for Perception of Speech and Visual Form. Cambridge: MIT Press, 1964.
Montanari U. Continuous skeletons from digitized images [J]. J Assoc, Comp Machinery, 1969, 16(4): 534–549.
Bitz G, Kung H T. Path planning on the warp computer: Using a linear systolic array in dynamic programming [J]. Int’l J Computer Mathematics, 1988, 25: 173–188.
Kimmel R. Skeletonization via distance maps and level sets [J]. Computer Vision and Image Understanding, 1995, 62(3): 382–391.
Leymarie F, Levine M D. Simulating the grassfire transform using an active contour model [J]. In IEEE Trans PAMI, 1992, 14(1): 56–75.
Brandt J W, Algazi V R. Continuous skeleton computation by voronoi diagram [J]. CVGIP: Image Understanding, 1994, 55: 329–338.
Ogniewicz R L. Discrete voronoi skeletons [M]. Konstanz, Germany: Hartung-Gorre Verlag, 1993.
Liu T L, Geiger D, Kohn R V. Representation and self-similarity of shapes[C]//Proceedings of the Sixth International Conference on Computer Vision. Washington: IEEE Computer Society, 1999: 1129–1135.
Golland P, Eric W, Grimson L. Fixed topology skeleton[C]//Proceedings of the IEEE Computer Society Conference on Computer Visionand Pattern Recognftion. [s.l.]: IEEE, 2000: 10–17.
Ejiri M, Kakumoto S, Miyatake T, et al. Automatic recognition of design drawings and maps[C]//in Proc Seventh Int. Conf Pattern Recognition. Montreal: [s.n.], 1984: 1296–1305.
Kasturi R, Bow S T, El-Masri W, et al. A system for interpretation of line drawings [J]. IEEE Transactions on PAMI, 1990, 12(10): 978–992.
Suzuki S, Yamada T. MARIS: Map recognition input system [J]. Pattern Recognition, 1990, 23(8): 919–933.
Nagao T, Agui T, Nakajima M. An automatic road vector extraction method from maps [C]//inProc Seventh Int. Conf Pattern Recognition. Montreal: [s.n.], 1988: 585–587.
Liu Yuncai. An automation system: Generation of digital map data from pictorial resources [J]. Pattern Recognition, 2002, 35(9): 1973–1987.
Bin D, Cheong W. A system for automatic extraction of road network from maps [C]//IEEE Proceedings, Intelligence and Systems. Washington DC: IEEE Computer Society, 1998: 359–366.
Itonaga W, Matsuda I, Yoneyama N, et al. Automatic extraction of road networks from map image [J]. Electronics and Communications in Japan, Part 2, 2003, 86(4): 62–72.
Wolter F E. Cut locus and medial axis in global shape interrogation and representation [R]. MIT Design Laboratory Memorandum 92-2, Massachusettes: MIT Ocean Engineering Design Laboratory, 1992.
Chang J S, Yap C K. A polynomial solution for the potato-peeling problem [J]. Discrete & Computational Geometry, 1986, 1(1): 155–182.
Chen M, Cheng Z G, Liu Y C. A robust algorithm of principal curve detection [C]//ICPR. Washington DC: IEEE Computer Society, 2004: 429–432.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, M., Liu, Yc. Connection skeleton extraction based on contour connectedness. J. Shanghai Jiaotong Univ. (Sci.) 13, 521–527 (2008). https://doi.org/10.1007/s12204-008-0521-x
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12204-008-0521-x