Canny edge detector: Difference between revisions
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imIn.cannyEdgeDetection(45, 50, 1.0f).savePGM("lena_canny.pgm"); |
imIn.cannyEdgeDetection(45, 50, 1.0f).savePGM("lena_canny.pgm"); |
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}</lang> |
}</lang> |
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=={{header|Go}}== |
=={{header|Go}}== |
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<lang MATLAB>BWImage = edge(GrayscaleImage,'canny');</lang> |
<lang MATLAB>BWImage = edge(GrayscaleImage,'canny');</lang> |
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=={{ |
=={{header|Phix}}== |
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{{improve|Phix|Port to pGUI for linux and 64 bit compatibility.}} |
{{improve|Phix|Port to pGUI for linux and 64 bit compatibility.}} |
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The file demo\Arwen32dibdemo\manip.exw in the standard distribution contains a menu entry for this, Manipulate/Filter/Detect Edges, along with 15 or so other effects. It is however windows-32-bit only, and could do with being ported to pGUI. |
The file demo\Arwen32dibdemo\manip.exw in the standard distribution contains a menu entry for this, Manipulate/Filter/Detect Edges, along with 15 or so other effects. It is however windows-32-bit only, and could do with being ported to pGUI. |
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=={{ |
=={{header|Python}}== |
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In Python, Canny edge detection would normally be done using [http://scikit-image.org/docs/dev/auto_examples/plot_canny.html scikit-image] or OpenCV-Python. Here is an approach using numpy/scipy: |
In Python, Canny edge detection would normally be done using [http://scikit-image.org/docs/dev/auto_examples/plot_canny.html scikit-image] or OpenCV-Python. Here is an approach using numpy/scipy: |
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