Multiprimitive segmentation based on meaningful breakpoints for fitting digital planar curves with line segments and conic arcs

Authors:
Wu-Chih Hu
Affiliations:
Department of Computer Science and Information Engineering, National Penghu Institute of Technology, #300, Liu-Ho Road, Makung City, Penghu, Taiwan, ROC
Venue:
Image and Vision Computing
Year:
2005

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Abstract

This paper presents a multiprimitive segmentation method with line segments and conic arcs based on the types of breakpoints. In this method, a joint tuning procedure is proposed to merge consecutive segments and adjust their locations to achieve more accurate and stable conic arcs. No threshold is required in the multiprimitive segmentation by using the proposed scheme. And, the types of breakpoints among line segments and conic arcs are defined and they are useful and meaningful for pattern recognition and shape analysis. Besides, the computational complexity of the proposed method is O(n log n) which is lower than most other conic fitting methods. Further, the concept of types of breakpoints can be easily extended to other primitives.