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Mathematical Problems in Engineering
Volume 2014, Article ID 378159, 10 pages
http://dx.doi.org/10.1155/2014/378159
Research Article

Effective Volumetric Feature Modeling and Coarse Correspondence via Improved 3DSIFT and Spectral Matching

1Xiamen University of Technology, Xiamen 361024, China
2Louisiana State University, Baton Rouge, LA 70803, USA

Received 12 July 2014; Revised 1 October 2014; Accepted 1 October 2014; Published 20 October 2014

Academic Editor: Erik Cuevas

Copyright © 2014 Peizhi Chen and Xin Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents a nonrigid coarse correspondence computation algorithm for volumetric images. Our matching algorithm first extracts then correlates image features based on a revised and improved 3DSIFT (I3DSIFT) algorithm. With a scale-related keypoint reorientation and descriptor construction, this feature correlation is less sensitive to image rotation and scaling. Then, we present an improved spectral matching (ISM) algorithm on correlated features to obtain a one-to-one mapping between corresponded features. One can effectively extend this feature correspondence to dense correspondence between volume images. Our algorithm can benefit nonrigid volumetric image registration in many tasks such as motion modeling in medical image analysis and processing.