Communications - Scientific Letters of the University of Zilina 2009, 11(4):65-68 | DOI: 10.26552/com.C.2009.4.65-68

General Vectorization of Line Objects in Drawn Maps

Peter Tarabek1
1 Department of Transportation Networks, Faculty of Management Science and Informatics, University of Zilina, Slovakia

Drawn maps consist of multiple object types. The most important are line objects which represent infrastructure. Attributes of these objects are essential for many tasks but in raster format they provide only low level information. Vectorization must be used to obtain vector data. In this paper general vectorization process consisting of five stages is proposed. For these stages short discussion and basic recommendations are given and some proper methods are presented.

Keywords: vectorization, skeletonization, skeleton, thinning, raster-to-vector

Published: December 31, 2009  Show citation

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Tarabek, P. (2009). General Vectorization of Line Objects in Drawn Maps. Communications - Scientific Letters of the University of Zilina, 11(4), 65-68. doi: 10.26552/com.C.2009.4.65-68
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    References

    1. DORI, D., LIU, W.: Sparse Pixel Vectorization: An Algorithm and Its Performance Evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, 1999, ISSN 0162-8828, pp. 202-215. Go to original source...
    2. TOMBRE, K., AH-SOON, C., DOSCH, P., MASINI, G., TABBONE, S.: Stable and Robust Vectorization: How to Make the Right Choices, Graphics Recognition-Recent Advances, 2000, ISBN 978-3-540-41222-9, pp. 3-18. Go to original source...
    3. HORI, O., TANIGAWA, S.: Raster-to-Vector Conversion by Line Fitting Based on Contours and Skeletons, Proceedings of the Second International Conference on Document Analysis and Recognition, 1993, pp. 353-358. Go to original source...
    4. ZOU, J. J., HONG, Y.: Vectorization of Cartoon Drawings, Selected papers from the Pan-Sydney workshop on Visualisation - Volume 2, 2000, ISSN 1445-1336, pp. 77-78.
    5. SUZUKI, S., UEDA, N.: Robust Vectorization Using Graph-Based Thinning And Reliability-Based Line Approximation, Proceedings CVPR '91, 1991, ISBN 0-8186-2148-6, pp. 494-500. Go to original source...
    6. BERNARD, T. M., MANZANERA, A.: Improved Low Complexity Fully Parallel Thinning Algorithm, In Proceedings of the 10th international Conference on Image Analysis and Processing, 1999, ISBN 0-7695-0040-4. Go to original source...
    7. ZHANG, T. Y., SUEN, C. Y.: A fast parallel algorithm for thinning digital patterns, Commun. ACM, 27(3), 1984, ISSN 0001-0782, pp. 236-239. Go to original source...
    8. LAM, L., LEE, S., SUEN, C. Y.: Thinning Methodologies-A Comprehensive Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 9, 1992, ISSN 0162-8828, pp. 869-885. Go to original source...
    9. BOBIN, J., STARCK, J.-L., FADILI, J., MOUDDEN, Y., DONOHO, D.L.: Morphological Component Analysis: an adaptative thresholding strategy, IEEE Transactions on Image Processing, Vol. 16, No. 11, 2007, ISSN 1057-7149, pp. 2675-2681. Go to original source...
    10. OTSU, N.: A threshold selection method from gray-level histogram, IEEE Transactions on System, Man and Cybernetics, Vol. 9, No. 1, 1979, ISSN 0018-9472, pp. 62-66. Go to original source...
    11. LIAO, P. S., CHEN, T. S., CHUNG, P. C.: A fast Algorithm for Multilevel Thresholding, Journal of Information Science and Engineering 17, 2001, pp. 713-727.
    12. TARABEK, P.: Morphology image pre-processing for thinning algorithms, Journal of Information, Control and Management Systems, Vol. 5, No.1, 2007, ISSN 1336-1716, pp. 131-138.
    13. TARABEK, P.: Performance measurements of thinning algorithms, Journal of Information, Control and Management Systems, Vol. 6, No. 2, 2008, ISSN 1336-1716, pp. 125-132.
    14. TARABEK, P.: A Contour Approach to Thinning Algorithms, Communications - Scientific Letters of the University of Zilina, Vol. 11, 3/2009, ISSN 1335-4205, pp. 43-48. Go to original source...
    15. KOLESNIKOV, A., FRANTI, P.: Data Reduction of Large Vector Graphics, Research Report, A-2003-2, Department of Computer Science, University of Joensuu, Finland, 2003, ISBN 952-458-311-9.
    16. SARFRAZ, M.: Optimal Curve Fitting to Digital Data, International Journal of WSCG, Vol. 11, No. 1, 2003, ISSN 1213-6972.
    17. DOSCH, P., MASINI, G., TOMBRE, K.: Improving Arc Detection in Graphics Recognition, Proc. 15th Int'l Conf. Pattern Recognition (ICPR '00), Vol. 2, 2000, ISBN 0-7695-0750-6, pp. 243-246. Go to original source...

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