Application of Affine-Invariant Fourier Descriptors to Recognition of 3-D Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric heat equation and nonlinear diffusion of shapes and images
Computer Vision and Image Understanding
Reliable Classification of Chrysanthemum Leaves through Curvature Scale Space
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
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The maxima of Curvature Scale Space (CSS) image have already been used to represent 2-D shapes under affine transforms. Since the CSS image employs the arc length parametrisation which is not affine invariant, we expect some deviation in the maxima of the CSS image under general affine transforms. In this paper we examine the advantage of using affine length rather than arc length to parametrise the curve prior to computing its CSS image. The parametrisation has been proven to be invariant under affine transformation and has been used in many affine invariant shape recognition methods. The CSS representation with affine length parametrisation has been used to find similar shapes from a large prototype database.