Paper Info
Title
A Systematic Design Procedure for Scalable Near-Circular Laplacian of Gaussian Operators
Abstract
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.
Year
DOI
Venue
2004
10.1109/ICPR.2004.109
ICPR (1)
Keywords
Field
DocType
near-circular low-level laplacian image,finite element method,circular differential edge operator,scalable near-circular laplacian,gaussian operators,low-level image processing task,image gradient direction,systematic design procedure,gaussian operator,general approach,general design technique,laplacian operator,gaussian basis function,gaussian processes,image processing,laplacian of gaussian,edge detection,mesh generation,feature extraction
Laplacian smoothing,Mathematical Operators,Computer science,Scale space,Artificial intelligence,Operator (computer programming),Blob detection,Gaussian function,Mathematical optimization,Pattern recognition,Algorithm,Gaussian blur,Laplace operator
Conference
ISSN
ISBN
Citations 
1051-4651
0-7695-2128-2
12
PageRank 
References 
Authors
0.94
7
3
Name
Order
Citations
PageRank
S. A. Coleman1408.50
B. W. Scotney2536.56
M. G. Herron3445.21