Shape Classification using Multiscale Fourier-based Description in 2-D Space
Direkoglu, Cem and Nixon, Mark S. (2008) Shape Classification using Multiscale Fourier-based Description in 2-D Space. At IEEE International Conference on Signal Processing (ICSP 2008), Beijing, China,
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Description/Abstract
In shape recognition, the boundary and exterior parts are amongst the most discriminative features. In this paper, we propose new multiscale Fourier-based object descriptors in 2-D space, which represents the boundary and exterior parts of an object more than the central part. This representation is based on using a high-pass Gaussian filter at different scales. The proposed algorithm makes descriptors size, translation and rotation invariant as well as increasing discriminative power and immunity to noise. In comparison, the new algorithm performs better than elliptic Fourier descriptors and Zernike moments with respect to increasing noise.
| Item Type: | Conference or Workshop Item (Speech) |
|---|---|
| Additional Information: | Event Dates: October 2008 |
| Divisions: | Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 266817 |
| Date Deposited: | 21 Oct 2008 14:48 |
| Last Modified: | 01 Mar 2012 11:47 |
| Contributors: | Direkoglu, Cem (Author) Nixon, Mark S. (Author) |
| Date: | 2008 |
| Additional Information: | Event Dates: October 2008 |
| Status: | Published |
| Further Information: | Google Scholar |
| ISI Citation Count: | 3 |
| URI: | http://eprints.soton.ac.uk/id/eprint/266817 |
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