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.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | IEEE Signal Processing Society |
Pages | 844-847 |
Number of pages | 4 |
Volume | 3 |
DOIs | |
Publication status | Published (in print/issue) - Oct 2001 |
Event | IEEE International Conference on Image Processing (ICIP 2001) - Thessaloniki, Greece Duration: 1 Oct 2001 → … |
Conference
Conference | IEEE International Conference on Image Processing (ICIP 2001) |
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Period | 1/10/01 → … |
Keywords
- Image derivative operators
- circularity
- angular error
- near-circular operators
- low-level feature extraction