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Direct Curvature Scale Space: Theory and Corner Detection

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2 Author(s)
Baojiang Zhong ; Dept. of Math., Nanjing Univ. of Aeronaut. & Astronaut. ; Wenhe Liao

The curvature scale space (CSS) technique is considered to be a modern tool in image processing and computer vision. direct curvature scale space (DCSS) is defined as the CSS that results from convolving the curvature of a planar curve with a Gaussian kernel directly. In this paper we present a theoretical analysis of DCSS in detecting corners on planar curves. The scale space behavior of isolated single and double corner models is investigated and a number of model properties are specified which enable us to transform a DCSS image into a tree organization and, so that corners can be detected in a multiscale sense. To overcome the sensitivity of DCSS to noise, a hybrid strategy to apply CSS and DCSS is suggested

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:29 ,  Issue: 3 )

Date of Publication:

March 2007

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