• 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