Technical Section: Automatic fitting of digitised contours at multiple scales through the curvature scale space technique

  • Authors:

  • Farzin Mokhtarian;Yoke Khim Ung;Zhitao Wang

  • Affiliations:

  • Centre for Vision, Speech and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK;Centre for Vision, Speech and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK;Centre for Vision, Speech and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK

  • Venue:
  • Computers and Graphics
  • Year:
  • 2005

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Abstract

The curvature scale space (CSS) technique has been used in conjunction with Hermite curves for automatic fitting of digitised contours at multiple scales. CSS is a powerful contour shape descriptor which has been selected for MPEG-7 standardisation. Hermite curves were used since each Hermite curve is defined by two endpoints and the tangent vectors at those points. No points external to the input contour are required for Hermite curves. Hermite endpoints are defined as consecutive curvature zero-crossing points extracted at multiple scales using the CSS method. Hermite tangent vectors can also be determined using the CSS technique. Approximation error and compression ratio are computed at each scale. The graph of compression ratio as a function of approximation error is smoothed to remove noise. The bending point of that function is defined as the largest maximum of its second derivative. This point can be considered as the boundary between the mostly vertical and the mostly horizontal segments of the graph. It can be used for automatic selection of an optimal scale. Finally, the original contour reconstruction technique has been extended to improve the quality of fit. This has been achieved by adjusting the lengths of tangent vectors for each spline segment independently.