Noise-Resistant Invariants of Curves

Projective invariants are shape descriptors that are independent of the point of view from which the shape is seen, and, therefore, are of major importance in object recognition. They make it possible to match an image of an object to one stored in a database without the need for searching for the correct viewpoint. An invariant representation of a general curve is obtained. The calculation is local and does not suffer from the occlusion problem of global descriptors. To make the method robust, differentiation techniques that give much more reliable results than previous ones are developed. These differentiation methods are useful in many other applications as well. >

[1]  Isaac Weiss,et al.  Smoothed differentiation filters for images , 1992, J. Vis. Commun. Image Represent..

[2]  Eamon B. Barrett,et al.  General methods for determining projective invariants in imagery , 1991, CVGIP Image Underst..

[3]  Isaac Weiss,et al.  Projective invariants of shapes , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  David A. Forsyth,et al.  Invariant Descriptors for 3D Object Recognition and Pose , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  J.B. Burns,et al.  View Variation of Point-Set and Line-Segment Features , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Johan Wagemans,et al.  Similarity extraction and modeling , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[7]  A. Bruckstein,et al.  Differential invariants of planar curves and recognizing partially occluded shapes , 1992 .

[8]  Christopher M. Brown Numerical evaluation of differential and semi-differential invariants , 1992 .

[9]  V. G. Grove,et al.  A Treatise On Projective Differential Geometry , 1942 .

[10]  Isaac Weiss Noise resistant projective and affine invariants , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.