Two Novel Complete Sets of Similarity Invariants

This source preferred by Hongchuan Yu

Authors: Yu, H. and Bennamoun, M.

http://www.springerlink.com/content/p64351t316qm3tk3/

Pages: 659-665

Publisher: Springer

Place of Publication: Berlin / Heidelberg

ISBN: 978-3-540-30750-1

DOI: 10.1007/11595755_82

In this paper, we propose two complete sets of similarity invariant descriptors under the Fourier-Mellin Transform and the Analytical Fourier-Mellin Transform (AFMT) frameworks respectively. Furthermore, their numerical properties are presented and be revealed through image reconstruction. Experimental results indicate that our proposed invariant descriptors can fully reconstruct the original image eliminating any existing similarity transformation (such as rotation, translation and scale) from the original image.

This data was imported from Scopus:

Authors: Yu, H. and Bennamoun, M.

Volume: 3804 LNCS

Pages: 659-665

ISBN: 9783540307501

In this paper, we propose two complete sets of similarity invariant descriptors under the Fourier-Mellin Transform and the Analytical Fourier-Mellin Transform (AFMT) frameworks respectively. Furthermore, their numerical properties are presented and be revealed through image reconstruction. Experimental results indicate that our proposed invariant descriptors can fully reconstruct the original image eliminating any existing similarity transformation (such as rotation, translation and scale) from the original image. © Springer-Verlag Berlin Heidelberg 2005.

The data on this page was last updated at 04:53 on March 24, 2019.