Edge detection: Difference between revisions

Revision as of 15:59, 30 January 2006

Revision as of 16:50, 2 February 2006

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* 2nd Order: [[Laplacian]], [[Marr-Hildreth algorithm|Marr-Hildreth]], [[zero-crossing]]s of the second-order derivative in the gradient direction.

Currently, the [[Canny|Canny operator]] (or variations of this operator) is most commonly used edge detection method. A large number of edge detection operators have been published but so far none has shown significant advantages over the Canny operator in general situations.

In his original work, Canny studied the problem of designing an optimal pre-[[smoothing]] filter for edge detection, and then showed that this filter could be well approximated by a first-order [[Gaussian function|Gaussian derivative kernel]].

Canny also introduced the notion of non-maximum suppression, which means that edges are defined as points where the gradient magnitude assumes a maximum in the gradient direction.

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where <math>L_x</math>, <math>L_y</math> ... <math>L_{yyy}</math> denote partial derivatives computed from

a [[scale-space]] representation <math>L</math> obtained by smoothing the original image with a Gaussian kernel.

==See also==