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A Systematic Design Procedure for Scalable Near-Circular Gaussian Operators

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Scotney, BW, Coleman, SA and Herron, MG (2001) A Systematic Design Procedure for Scalable Near-Circular Gaussian Operators. In: IEEE International Conference on Image Processing (ICIP 2001), Thessaloniki, Greece. IEEE Signal Processing Society. Vol 3 4 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1109/ICIP.2001.958252

Abstract

In image filtering, the 'circularity' of an operator is an important factor affecting its accuracy. For example, circular differential edge operators are effective in minimising the angular error in the estimation of image gradient direction. We present a general approach to the computation of scalable circular low-level image processing operators that is based on the finite element method. We show that the use of Gaussian basis functions within the finite element method provides a framework for a systematic and efficient design procedure for operators that are scalable to near-circular neighbourhoods through the use of an explicit scale parameter. The general design technique may be applied to a range of operators. Here we evaluate the approach for the design of an image gradient operator, and we present comparative results with other gradient approximation methods.

Item Type:Conference contribution (Paper)
Keywords:Image derivative operators, circularity, angular error, near-circular operators, low-level feature extraction
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:6774
Deposited By:Professor Bryan Scotney
Deposited On:23 May 2011 15:36
Last Modified:23 May 2011 15:36

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