Image processing techniques for feature location

  • Andrew Blake
  • Michael Isard

Abstract

The use of image-filtering operations to highlight image features was illustrated in chapter 2. Figure 2.1 on page 27 illustrated operators for emphasising edges, valleys and ridges, and it was shown how the emphasised image could be used as a landscape for a snake. However, for efficiency, the deformable templates described in the next two chapters are driven towards a distinguished feature curve rf(s) rather than over the entire image landscape F that is used in the snake model. This is rather like making a quadratic approximation to the external snake energy:
$${E_{{\rm{ext}}}}\infty - F({\rm{r}})\infty \int {{{({\rm{r(}}s{\rm{) - }}{{\rm{r}}_f}(s))}^2}ds,} $$
where rf(s) lies along a ridge of the feature-map function F. The increase in efficiency comes from being able to move directly to the curve rf, rather than having to iterate towards it as in the original snake algorithm described in section 2.1.

Keywords

Expense Convolution Pyramid 

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Copyright information

© Springer-Verlag London Limited 1998

Authors and Affiliations

  • Andrew Blake
    • 1
  • Michael Isard
    • 1
  1. 1.Department of Engineering ScienceUniversity of OxfordOxfordUK

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