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Extracting Arbitrary Geometric Primitives Represented by Fourier Descriptors

Extracting Arbitrary Geometric Primitives Represented by Fourier Descriptors
Extracting Arbitrary Geometric Primitives Represented by Fourier Descriptors
In this paper we present a novel formulation for the extraction of arbitrary shapes in model-based recognition. The formulation is based on the mapping defined in the Hough transform. We develop this mapping for the analytic representation of a shape characterised by a Fourier parameterisation. Edge direction information is included in the formulation as a way of reducing the computational requirements in the extraction process. The proposed approach extends the analytic formulation of the Hough transform to arbitrary shapes which leads to an accurate and efficient evidence accumulation process. Experimental results show that the new approach can handle noise and occlusion in synthetic and real images.
547--551
Aguado, A.S.
ad7e99c5-47ab-4f88-849a-c6e6d77e4200
Montiel, M.E.
4aefa43d-aeb9-4151-83f5-31fbab5664ba
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Aguado, A.S.
ad7e99c5-47ab-4f88-849a-c6e6d77e4200
Montiel, M.E.
4aefa43d-aeb9-4151-83f5-31fbab5664ba
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Aguado, A.S., Montiel, M.E. and Nixon, M.S. (1996) Extracting Arbitrary Geometric Primitives Represented by Fourier Descriptors At Proc. International Conference on Pattern Recognition ICPR '96. , 547--551.

Record type: Conference or Workshop Item (Other)

Abstract

In this paper we present a novel formulation for the extraction of arbitrary shapes in model-based recognition. The formulation is based on the mapping defined in the Hough transform. We develop this mapping for the analytic representation of a shape characterised by a Fourier parameterisation. Edge direction information is included in the formulation as a way of reducing the computational requirements in the extraction process. The proposed approach extends the analytic formulation of the Hough transform to arbitrary shapes which leads to an accurate and efficient evidence accumulation process. Experimental results show that the new approach can handle noise and occlusion in synthetic and real images.

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More information

Published date: 1996
Additional Information: Address: Vienna
Venue - Dates: Proc. International Conference on Pattern Recognition ICPR '96, 1996-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250060
URI: http://eprints.soton.ac.uk/id/eprint/250060
PURE UUID: 4ccd3d37-e2ac-4269-88cd-8df7cef8bea3

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:44

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Contributors

Author: A.S. Aguado
Author: M.E. Montiel
Author: M.S. Nixon

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