Title :
Affine-invariant B-spline moments for curve matching
Author :
Huang, Zhaohui ; Cohen, Fernand S.
Author_Institution :
United Technol. Res. Center, East Hartford, CT, USA
fDate :
10/1/1996 12:00:00 AM
Abstract :
The article deals with the problem of matching and recognizing planar curves that are modeled by B-splines, independently of possible affine transformations to which the original curve has been subjected (for example, rotation, translation, scaling, orthographic, and semiperspective projections), and possible occlusion. It presents a fast algorithm for estimating the B-spline control points that is robust to nonuniform sampling, noise, and local deformations. Curve matching is achieved by using a similarity measure based on the B-spline knot points introduced by Cohen et al. (1991). This method, however, can neither handle the affine transformation between the curves nor the occlusion. Solutions to these two problems are presented through the use of a new class of weighted B-spline curve moments that are well defined for both open and closed curves. The method has been applied to classifying affine-transformed aircraft silhouettes, and appears to perform well
Keywords :
aircraft; edge detection; image classification; image matching; image recognition; image representation; image sampling; splines (mathematics); B-spline control points; B-spline knot points; affine invariant B-spline moments; affine transformation; aircraft silhouettes classification; closed curves; curve matching; curve recognition; curve representation; fast algorithm; local deformations; noise; nonuniform sampling; occlusion; open curves; orthographic projection; planar curves; rotation; scaling; semiperspective projections; similarity measure; translation; weighted B-spline curve moments; Aircraft; Controllability; Design automation; Fourier transforms; Noise robustness; Nonuniform sampling; Robust control; Shape control; Spline; Stochastic processes;
Journal_Title :
Image Processing, IEEE Transactions on