Edge Based Probabilistic Relaxation for Sub-pixel Contour Extraction

نویسندگان

  • Toshiro Kubota
  • Terrance L. Huntsberger
  • Jeffrey T. Martin
چکیده

The paper describes a robust edge and contour extraction technique under two types of degradation: random noise and aliasing. The technique employs unambiguous probabilistic relaxation to distinguish features from noise and refine their spatial locations at sub-pixel accuracy. The most important component in the probabilistic relaxation is a compatibility function. The paper suggests a function with which the optimal orientation of edges can be derived analytically, thus allowing an efficient implementation of the relaxation process. A contour extraction algorithm is designed by combining the relaxation process and a perceptual organization technique. Results on both synthetic and natural images are given and show effectiveness of our approach against noise and aliasing. keywords: feature extraction, relaxation labelling, segmentation

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تاریخ انتشار 2001