Shape retrieval through normalized B-splines curves

Shape retrieval through normalized B-splines curves This paper proposes a new technique for 2D shape modeling and retrieval based only on curves defined from shape boundary. Firstly, a shape representation system is build based on the decomposition of the outline into its constituent parts and their geometric description. The process decomposition is done using high curvature points located along the boundary. These obtained parts are then described by parametric curves using the B-spline approximation and normalized in order to eliminate scaling transformation. Finally, the resulting curves allow matching of shapes and retrieving that is robust to rotation, scale change and deformation. Experiments conducted on a variety of shape databases including Kimia-99, Kimia-216, MPEG-7 and our database created from a selection of ETH-80 shape database, illustrate the performance of the proposed approach when compared with existing algorithms in literature. Obtained results are presented and discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Shape retrieval through normalized B-splines curves

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-017-4998-x
Publisher site
See Article on Publisher Site

Abstract

This paper proposes a new technique for 2D shape modeling and retrieval based only on curves defined from shape boundary. Firstly, a shape representation system is build based on the decomposition of the outline into its constituent parts and their geometric description. The process decomposition is done using high curvature points located along the boundary. These obtained parts are then described by parametric curves using the B-spline approximation and normalized in order to eliminate scaling transformation. Finally, the resulting curves allow matching of shapes and retrieving that is robust to rotation, scale change and deformation. Experiments conducted on a variety of shape databases including Kimia-99, Kimia-216, MPEG-7 and our database created from a selection of ETH-80 shape database, illustrate the performance of the proposed approach when compared with existing algorithms in literature. Obtained results are presented and discussed.

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: Aug 15, 2017

References

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