Image-based Multiscale Shape Description using Gaussian Filter
Image-based Multiscale Shape Description using Gaussian Filter
In shape recognition, a multiscale description provides more information about the object, increases discrimination power and immunity to noise. In this paper, we develop a new multiscale Fourier-based object description in 2-D space using a low-pass Gaussian filter (LPGF) and a high-pass Gaussian filter (HPGF), separately. Using the LPGF, at different scales, represents the inner and central part of an object more than the boundary. On the other hand using the HPGF, at different scales, represents the boundary and exterior parts of an object more than the central part. Our algorithms are also organized to achieve size, translation and rotation invariance. Evaluation indicates that representing the boundary and exterior parts more than the central part using the HPGF performs better than the LPGF based multiscale representation, and in comparison to Zernike moments and elliptic Fourier descriptors with respect to increasing noise.
Direkoglu, Cem
b793e59b-4188-44b2-99c5-b4dedc46cfda
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
2008
Direkoglu, Cem
b793e59b-4188-44b2-99c5-b4dedc46cfda
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Direkoglu, Cem and Nixon, Mark S.
(2008)
Image-based Multiscale Shape Description using Gaussian Filter.
IEEE Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2008), Bhubaneswar, India.
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Conference or Workshop Item
(Poster)
Abstract
In shape recognition, a multiscale description provides more information about the object, increases discrimination power and immunity to noise. In this paper, we develop a new multiscale Fourier-based object description in 2-D space using a low-pass Gaussian filter (LPGF) and a high-pass Gaussian filter (HPGF), separately. Using the LPGF, at different scales, represents the inner and central part of an object more than the boundary. On the other hand using the HPGF, at different scales, represents the boundary and exterior parts of an object more than the central part. Our algorithms are also organized to achieve size, translation and rotation invariance. Evaluation indicates that representing the boundary and exterior parts more than the central part using the HPGF performs better than the LPGF based multiscale representation, and in comparison to Zernike moments and elliptic Fourier descriptors with respect to increasing noise.
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Published date: 2008
Additional Information:
Event Dates: December 2008
Venue - Dates:
IEEE Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2008), Bhubaneswar, India, 2008-12-01
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 266818
URI: http://eprints.soton.ac.uk/id/eprint/266818
PURE UUID: 7aeb35bd-f91b-4f76-be52-7a8af377306e
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Date deposited: 21 Oct 2008 14:57
Last modified: 15 Mar 2024 02:35
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Author:
Cem Direkoglu
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