Edge Detection
Find edges of objects in images using Sobel, Prewitt, Roberts, or Canny method
Libraries:
Computer Vision Toolbox /
Analysis & Enhancement
Description
The Edge Detection block finds edges of objects in an input image. The block supports four methods: Sobel, Prewitt, Roberts, and Canny. The first three methods find the edges by approximating the gradient magnitude of the image. The block convolves the input matrix with the Sobel, Prewitt, or Roberts kernel respectively, and outputs the resulting gradient components of the image. Additionally, the block outputs a binary image of the edge detections by thresholding the gradient magnitude.
The Canny method computes the gradient of input image using the derivative of the Gaussian filter. It then finds edges by looking for the local maxima of the gradient. This method uses two thresholds to detect the strong and weak edges. The weak edges are part of the output only if they are connected to strong edges. The block outputs a binary image of the edge detections for this method.
Examples
Ports
Input
Output
Parameters
Block Characteristics
Data Types |
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Multidimensional Signals |
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Variable-Size Signals |
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References
[1] Gonzales, Rafael C. and Richard E. Woods. Digital Image Processing. 2nd ed. Englewood Cliffs, NJ: Prentice Hall, 2002.
[2] Pratt, William K. Digital Image Processing, 2nd ed. NY: John Wiley & Sons, 1991.
Extended Capabilities
Version History
Introduced before R2006a