Coleman, SA, Scotney, BW and Herron, MG (2004) A Systematic Design Procedure for Scalable Near-Circular Laplacian of Gaussian Operators. In: 17th IEEE International Conference on Pattern Recognition (ICPR 2004), Cambridge. IEEE Computer Society. Vol 1 4 pp. [Conference contribution]
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In low-level image processing tasks, the circularity of an operator has been shown to be an important factor affecting its accuracy as 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 near-circular low-level Laplacian image processing operators that is based on the finite element method. We use Gaussian basis functions, together with a virtual finite element mesh, to illustrate the design of 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 illustrate the approach by discussing the implementation of a Laplacian operator, and we evaluate our approach by presenting comparative results with the Laplacian of Gaussian operators.
|Item Type:||Conference contribution (Paper)|
|Keywords:||feature extraction, Laplacian of Gaussian, near-circular operators, scalable operators|
|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
|Deposited By:||Professor Bryan Scotney|
|Deposited On:||23 May 2011 15:41|
|Last Modified:||23 May 2011 15:41|
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