Edge Detection

Class: NodeCannyFilter

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Based on John Canny's paper “A Computational Approach to Edge Detection”(IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No.6, November 1986), there are four major steps used in the edge-detection scheme: (1) Smooth the input image with Gaussian filter. (2) Calculate the second directional derivatives of the smoothed image. (3) Non-Maximum Suppression: the zero-crossings of 2nd derivative are found, and the sign of third derivative is used to find the correct extrema. (4) The hysteresis thresholding is applied to the gradient magnitude (multiplied with zero-crossings) of the smoothed image to find and link edges.

Inputs

Image

Input image.

Type: Image4DFloat, Required, Single

Outputs

Output

Resulting image.

Type: Image4DFloat

Settings

Lower Threshold Number

Define the lower threshold for detection edges.

Upper Threshold Number

Define the upper threshold for detection edges.

Variance Number

Set the variance of the Gaussian smoothing filter.

Maximum Error Number

Set the MaximumError parameter used by the Gaussian smoothing filter in this algorithm.

References

Canny edge detection in SimpleITK

Keywords: Canny, edge, edge-detection