DocumentCode :
1545985
Title :
Multiprimitive segmentation of planar curves-a two-level breakpoint classification and tuning approach
Author :
Sheu, Hsin-Teng ; Hu, Wu-Chih
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ. of Technol., Taipei, Taiwan
Volume :
21
Issue :
8
fYear :
1999
fDate :
8/1/1999 12:00:00 AM
Firstpage :
791
Lastpage :
797
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 are 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
Keywords :
image classification; image segmentation; optical tuning; pattern matching; quantisation (signal); benchmark; breakpoint classification; curvature; joint tuning; multiprimitive segmentation; pattern matching; pattern recognition; planar curves; projective height; quantization; smooth joints; tuning; Algorithm design and analysis; Benchmark testing; Curve fitting; Doped fiber amplifiers; Image processing; Image segmentation; Phase detection; Phase noise; Quantization; Robustness;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.784310
Filename :
784310
Link To Document :
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