Scotney, BW and Coleman, SA (2007) Improving Angular Error via Systematically Designed Near-circular Gaussian-based Feature Extraction Operators. Pattern Recognition, 40 (5). pp. 1451-1465. [Journal article]
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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 the image gradient operator. We illustrate that this design procedure significantly reduces angular error in comparison to other well-known gradient approximation methods.
|Item Type:||Journal article|
|Keywords:||Circularity; Angular error; 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
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
|Deposited By:||Professor Bryan Scotney|
|Deposited On:||27 Sep 2009 15:13|
|Last Modified:||15 Jun 2011 11:08|
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