Multiprimitive Segmentation of Planar Curves-A Two-Level Breakpoint Classification and Tuning Approach

Authors:
Hsin-Teng Sheu;Wu-Chih Hu
Affiliations:
National Taiwan Univ. of Science and Technology, Taipei,Taiwan, Republic of China;National Penghu Institute of Marine and Management Technology, Penghu, Taiwan, Rebublic of China
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1999

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Abstract

A breakpoint classification and tuning approach is proposed for the multiprimitive segmentation of planar curves, and cockhead-like graph is suggested to evaluate the multiprimitive segmentation algorithms. The breakpoints are divided into corners and smooth joints and the types of the segments on both sides of a breakpoint are identified. Then, a joint tuning procedure is exercised to merge/split segments and adjust the joint locations. The carefully designed cockhead-like graph includes all possible combinations and parameters of line and arc segments and serves as a benchmark to test the algorithms. The proposed scheme is simple, fast, threshold-free and robust to quantization and preprocessing errors, thus allowing it to be employed in a variety of applications such as matching and recognition. Test against the suggested benchmark and comparison with those in the literature assures the superiority of the method suggested herein.