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Improving Angular Error by Near Circular Operator Design

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

Scotney, BW, Coleman, SA and Herron, MG (2004) Improving Angular Error by Near Circular Operator Design. Pattern Recognition, 37 (1). pp. 169-172. [Journal article]

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URL: http://dx.doi.org/10.1016/j.patcog.2003.07.001

DOI: 10.1016/j.patcog.2003.07.001

Abstract

In image filtering, the circularity of an operator is an important factor affecting its accuracy. When step edge orientation is estimated in a square neighbourhood, the use of standard methods can result in a detected orientation error of up to 6.6% [2]. Circular differential edge operators are effective in minimising this angular error and may in fact reduce it to zero for all orientations [2]. The principles of circularity [2] and scale (see, for example, [4]) are amongst the principal considerations when designing low-level image processing operators. When coupled with the task of designing optimal discrete Gaussian operators [1], such considerations become both particularly relevant and challenging. In this paper, we show how the adoption of a finite-element-based approach allows us to formulate a design procedure that can embrace all three aspects: circularity, scale and Gaussian approximation. Via the use of edge sensitivity analysis, we show that such a design procedure can significantly improve detected edge orientation over a full range of orientations and displacements compared with standard operators.

Item Type:Journal article
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:6805
Deposited By:Professor Bryan Scotney
Deposited On:20 Jan 2010 15:47
Last Modified:15 Jun 2011 11:08

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