Canny edge detector: Difference between revisions

# '''Noise reduction.''' &nbsp; May be performed by [[wp:Gaussian blur|Gaussian filter]]. <br> &nbsp;

# Compute '''intensity gradient''' &nbsp; (matrices <math>G_x</math> and <math>G_y</math>) &nbsp; and its '''magnitude''' &nbsp; <math>G</math>:<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <math>G=\sqrt{G_x^2+G_y^2}</math><br>May be performed by [[image convolution|convolution of an image]] with [[wp:Sobel operator|Sobel operators]]. <br> &nbsp;

# '''Non-maximum suppression.''' &nbsp; <br>For each pixel compute the orientation of intensity gradient vector: &nbsp; <math>\theta = {\rm atan2}\left(G_y, \, G_x\right)</math>. &nbsp; &nbsp; <br>Transform &nbsp; angle <math>\theta</math> &nbsp; to one of four directions: &nbsp; 0,&nbsp;45,&nbsp;90,&nbsp;135&nbsp;degrees. &nbsp; &nbsp; <br>Compute new array &nbsp; <math>N</math>: &nbsp; &nbsp; if &nbsp; &nbsp; &nbsp; &nbsp; <math>G\left(p_a\right)<G\left(p\right)<G\left(p_b\right)</math><br>where &nbsp; <math>p</math> &nbsp; is the current pixel, &nbsp; <math>p_a</math> &nbsp; and &nbsp; <math>p_b</math> &nbsp; are the two neighbour pixels in the direction of gradient, &nbsp; <br>then &nbsp; &nbsp; <math>N(p) = G(p)</math>, &nbsp; &nbsp; &nbsp; otherwise &nbsp; <math>N(p) = 0</math>. &nbsp; <br>Nonzero pixels in resulting array correspond to local maxima of &nbsp; <math>G</math> &nbsp; in direction &nbsp; <math>\theta(p)</math>. <br> &nbsp;

# '''Tracing edges with hysteresis.''' &nbsp; <br>At this stage two thresholds for the values of &nbsp; <math>G</math> &nbsp; are introduced: &nbsp; <math>T_{min}</math> &nbsp; and &nbsp; <math>T_{max}</math>. &nbsp; <br>Starting from pixels with &nbsp; <math>N(p) \geqslant T_{max}</math>, &nbsp; <br>find all paths of pixels with &nbsp; <math>N(p) \geqslant T_{min}</math> &nbsp; and put them to the resulting image.

<langsyntaxhighlight lang="c">#include <stdint.h>

}</langsyntaxhighlight>

<langsyntaxhighlight lang="d">import core.stdc.stdio, std.math, std.typecons, std.string, std.conv,

}</langsyntaxhighlight>

<langsyntaxhighlight lang="go">package main

}</langsyntaxhighlight>

<langsyntaxhighlight Jlang="j">NB. 2D convolution, filtering, ...

run''</langsyntaxhighlight>

El código es de Tom Gibara [The code is from Tom Gibara] (http://www.tomgibara.com/)

Se implementa utilizando una sola clase Java. [It is implemented using a single Java class.]

<langsyntaxhighlight Javalang="java">import java.awt.image.BufferedImage;

}</langsyntaxhighlight>

<langsyntaxhighlight lang="julia">using Images

<langsyntaxhighlight Mathematicalang="mathematica">Export["out.bmp", EdgeDetect[Import[InputString[]]]];</langsyntaxhighlight>

<langsyntaxhighlight MATLABlang="matlab">BWImage = edge(GrayscaleImage,'canny');</langsyntaxhighlight>

<langsyntaxhighlight Nimlang="nim">import lenientops

echo "Error: ", status.error</langsyntaxhighlight>

<langsyntaxhighlight lang="python">#!/bin/python

imshow(finalEdges)</langsyntaxhighlight>

<langsyntaxhighlight lang="tcl">package require crimp

cannyFilterFile {*}$argv</langsyntaxhighlight>