Journal Article10.1109/34.41386
Fast algorithms for low-level vision
507
TL;DR: A recursive filtering structure is proposed that drastically reduces the computational effort required for smoothing, performing the first and second directional derivatives, and carrying out the Laplacian of an image.
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Abstract: A recursive filtering structure is proposed that drastically reduces the computational effort required for smoothing, performing the first and second directional derivatives, and carrying out the Laplacian of an image. These operations are done with a fixed number of multiplications and additions per output point independently of the size of the neighborhood considered. The key to the approach is, first, the use of an exponentially based filter family and, second, the use of the recursive filtering. Applications to edge detection problems and multiresolution techniques are considered, and an edge detector allowing the extraction of zero-crossings of an image with only 14 operations per output element at any resolution is proposed. Various experimental results are shown. >
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References
Theory of Edge Detection
David Marr,Ellen C. Hildreth +1 more
TL;DR: The theory of edge detection explains several basic psychophysical findings, and the operation of forming oriented zero-crossing segments from the output of centre-surround ∇2G filters acting on the image forms the basis for a physiological model of simple cells.
7.3K
Scale-space filtering
Andrew Witkin
- 01 Jan 1987
TL;DR: Scale-space filtering is a method that describes signals qualitatively, managing the ambiguity of scale in an organized and natural way.
Using Canny's criteria to derive a recursively implemented optimal edge detector
TL;DR: It is shown that a solution to Canny's precise formulation of detection and localization for an infinite extent filter leads to an optimal operator in one dimension, which can be efficiently implemented by two recursive filters moving in opposite directions.
1.2K
Digital Step Edges from Zero Crossing of Second Directional Derivatives
TL;DR: The facet model is used to accomplish step edge detection and the Marr-Hildreth zero crossing of the Laplacian operator is found that it is the best performer; next is the Prewitt gradient operator.
Scale-space filtering: A new approach to multi-scale description
Andrew Witkin
- 19 Mar 1984
TL;DR: Scale-space filtering is a method that describes signals qualitatively, managing the ambiguity of scale in an organized and natural way.