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BMVC91 pp 319-322 | Cite as

Local Method for Curved Edges and Corners

  • R. T. Shann
  • J. P. Oakley
Conference paper

Abstract

A new method of detecting features in Gaussian smoothed images is described. Applied to the simple case of marking the Canny edge pixels the method gives an improved response at comers where traditional methods have problems. Moreover, the method permits marking of more sophisticated features at essentially no extra cost. Additional information available includes local curvature estimates for each edge, direct (local) identification of occluded edges and marking and characterising comers on edges. The performance of the method on real images is compared with the Plessey-Harris corner detector. We find that the quality and sensitivity of these comer detection methods are similar, with the new method giving information on the orientation and opening angle of the corners. Finally it is shown how ellipse detection in noisy images is made possible using this curvature information.

Keywords

Noisy Image Gradient Magnitude Canny Edge Canny Edge Detector Curvature Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Canny ‘Finding lines and edges in Images’ MIT Tech report 720 (1983)Google Scholar
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    Petrou ‘On the optimal edge detector’, Proceedings AVC88 191-196 (1988)Google Scholar
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    Shann & Oakley “Novel approach to boundary finding” IVC 8,32 (1990)Google Scholar
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    Torre & Poggio “On edge detection” IEEE TPAMI 2, 147 (1986)Google Scholar
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    Clark “Authenticating edges …” IEEE TPAMI 11, 43 (1989)Google Scholar
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    Harris ‘Combined corner and edge detectior’ Proceedings of AVC88p 147-152Google Scholar
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    Noble ‘Finding Corners’ IVC 6(2) 121–128 (1988)Google Scholar

Copyright information

© Springer-Verlag London Limited 1991

Authors and Affiliations

  • R. T. Shann
    • 1
  • J. P. Oakley
    • 1
  1. 1.Depts Medical Illustration & Electrical EngineeringUniversity of ManchesterManchesterUK

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