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Proceedings Paper

Affine-invariant moments and B-splines for object recognition from image curves
Author(s): Zhaohui Huang; Fernand S. Cohen
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Paper Abstract

In this paper we deal with the problem of matching and recognizing planar curves which are modeled as B-splines, independently of possible transformations that the original curve has been subjected to. Curve matching is achieved by using a finite set of B-spline moments which are compared to a set of B-spline prototype moments. When the observed curve is an unknown affine transformation (having four parameters) of one of the prototype curves, the affine parameters are estimated by relating the weighted moments of the original curve to that of the affine transformed curve. A set of up to a second order weighted B-spline moments are used toward that end, and results in a set of two single variable quadratic equations and two linear equations involving the four parameters of the linear transformation for which a closed form analytic expression exists. In the general linear case, the weight used is the affine length which weighs the moment integral by a kernel that results in having the affine parameters factoring out of the weighted moment integral. Once the transformation parameters are obtained, we undo the transformation, and use the set of third or fourth order B-spline moments for classification. The method is illustrated on classifying affine transformed silhouette of aircrafts.

Paper Details

Date Published: 11 March 1993
PDF: 11 pages
Proc. SPIE 1964, Applications of Artificial Intelligence 1993: Machine Vision and Robotics, (11 March 1993); doi: 10.1117/12.141768
Show Author Affiliations
Zhaohui Huang, Drexel Univ. (United States)
Fernand S. Cohen, Drexel Univ. (United States)


Published in SPIE Proceedings Vol. 1964:
Applications of Artificial Intelligence 1993: Machine Vision and Robotics
Kim L. Boyer; Louise Stark, Editor(s)

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