Canny Filter (2D)

A 2D Canny filter implementation by Vincent Morard. More...

Detailed Description

A 2D Canny filter implementation by Vincent Morard.

Canny edge detection: Canny's aim was to discover the optimal edge detection algorithm. In this situation, an "optimal" edge detector means:

• good detection - the algorithm should mark as many real edges in the image as possible.
• good localization - edges marked should be as close as possible to the edge in the real image.
• minimal response - a given edge in the image should only be marked once, and where possible, image noise should not create false edges.

To satisfy these requirements Canny used the calculus of variations - a technique which finds the function which optimizes a given functional.

The optimal function in Canny's detector is described by the sum of four exponential terms, but can be approximated by the first derivative of a Gaussian.

See also

• Canny Edge detector on Wikipedia
• John Canny, A computational approach to edge detection, IEEE Pami, vol. 8, n° 6, novembre 1986, pp 679-698

Author

Vincent Morard

Jose-Marcio Martins da Cruz (port from Morph-M)

Collaboration diagram for Canny Filter (2D):

Functions
template<class T1 , class T2 >
RES_T	cannyEdgeDetection (const Image< T1 > &imIn, const double sigma, Image< T2 > &imOut)
	cannyEdgeDetection Canny Filter

Function Documentation

cannyEdgeDetection()

template<class T1 , class T2 >

RES_T cannyEdgeDetection	(	const Image< T1 > &	imIn,
		const double	sigma,
		Image< T2 > &	imOut
	)

cannyEdgeDetection Canny Filter

Parameters

[in]	imIn	: input Image
[in]	sigma	:
[out]	imOut	: output Image