Scale-space techniques have been considered as modern tools for image understanding and analysis
because they are consistent with the concept of human beings, In this paper, a scale-space technique for shape
analysis based on the L curvature is proposed，and its applications in shape representation and corner detection arc
also studied. Analysis of its relation to planar curvature matched very well with experimental results. So, in
sometimes, L curvature takes place of real curvature. And Lcurvature has more advantage to real curvature.The
compute of L curvature is easy and accurate.Therefore, scale space based on L curvature has more merits. Multi-
scales L curvature products(MSCP) algorithms is introduced in detail.Then a new corner detector is proposed.
Extract zero crossings and the local extreme points of L curvature, and draw them in two plane coordinates, form
Curvature Scal}Space(CSS) maps.The CSS maps constructed with the L curvature indicate that the scale space
trajectories of zero crossings and the local extreme points arc stable with respect to the input parameter.
Experiments arc conducted which show that the new corner detector can enhance the information of shape feature
and suppress noise, and therefore can achieve a good performance in corner detection. Moreover, this method does
not have the undesirable effect of the Uaussian smoothing, need less calculation, have more robustness to noise.The
new corner detector is robust，simple and effective.
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