Abstract
Curvature Scale Space (CSS) representation of planar curves is considered to be a modern tool in image processing and shape analysis. Direct Curvature Scale Space (DCSS) is defined as CSS that results from convolving the curvature of a curve with a Gaussian kernel directly. Recently a theory of DCSS in corner detection has been established. In the present paper the DCSS theory is considered to transform the DCSS image of a given curve into a tree organization, and then corners on the curve are detected and located in a multiscale sense. Experiments are conducted to show that the DCSS corner detector can work equally well as the CSS corner detector does on curves with multiple-size features, however, at much less computational cost.
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Zhong, B., Liao, W. (2006). Direct Curvature Scale Space in Corner Detection. In: Yeung, DY., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2006. Lecture Notes in Computer Science, vol 4109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11815921_25
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DOI: https://doi.org/10.1007/11815921_25
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