Automated Generation Of Concatenated Arcs For Curve Representation

Sing T. Bow; Tsung-sheng Chen; S. Honnenahalli

doi:10.1117/12.960260

27 March 1989 Automated Generation Of Concatenated Arcs For Curve Representation

Sing T. Bow, Tsung-sheng Chen, S. Honnenahalli

Proceedings Volume 1002, Intelligent Robots and Computer Vision VII; (1989) https://doi.org/10.1117/12.960260
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

Effective representation of curves is an important aspect of pattern recognition. Extensive research has been done along this line by representing the curve with piecewise polynomial function of degree greater than one. Spline is a good example and is effective. Nevertheless, its mathematical representation still looks cumbersome. In this paper, an algorithm is designed to automatically generate a concise and rather accurate representation for curves in terms of concatenated arcs. Major idea is to efficiently and effectively detect the appropriate break points on the curves for the concatenated sections. Effectiveness of the algorithm has been evaluated through experiments on large number of various shapes. Results obtained are very satisfactory. For their descriptions, only one order of magnitude fewer segments are needed than those needed by linear approximation. Curves reconstructed from the descriptions match closely with the original ones, even for the very complex curves. Experiments were conducted on VAX 11/785 and also on our new PC-based image processing system. Results show that the algorithm is computationally very efficient. This system is useful in the archival and retrieval of graphic information, especially for the automatic handling of large amount of documents including text and graphics.

Citation Download Citation

Sing T. Bow, Tsung-sheng Chen, and S. Honnenahalli "Automated Generation Of Concatenated Arcs For Curve Representation", Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); https://doi.org/10.1117/12.960260

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