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
ePrint ID: 266817
Date Deposited: 21 Oct 2008 14:48
Last Modified: 27 Mar 2014 20:12
Further Information:Google Scholar
ISI Citation Count:3
URI: http://eprints.soton.ac.uk/id/eprint/266817

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