Conference proceeding
Affine-invariant B-spline moments for curve matching
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp 490-495
1994
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper deals with the problem of matching and recognizing planar curves which are modeled as B-splines. The paper presents a fast algorithm for estimating the control points of the B-spline which is robust to nonuniform sampling and noise. Curve matching is achieved by using the similarity measure based on the knot points associated with the B-spline curves. This method, however, can not handle the affine transformation and/or occlusion between the curves. This paper presents solutions to these two problems through the use of a new class of weighted B-spline curve moments that results in (1) a closed-form solution for the affine transformation parameters; (2) the starting and ending points of the segment on the prototype curve that was affine transformed to yield the observed curve. The method is used for classifying affine transformed silhouette of aircrafts, and appears to perform well.< >
Metrics
8 Record Views
Details
- Title
- Affine-invariant B-spline moments for curve matching
- Creators
- Zhaohui Huang - Drexel UniversityCohen - Drexel UniversityIEEE, COMPUTER SOC
- Publication Details
- 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp 490-495
- Publisher
- IEEE Comput. Soc. Press
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1994BA93D00070
- Other Identifier
- 991019184034404721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic