
.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/edges/plot_canny.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_edges_plot_canny.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_edges_plot_canny.py:


===================
Canny edge detector
===================

The Canny filter is a multi-stage edge detector. It uses a filter based on the
derivative of a Gaussian in order to compute the intensity of the gradients.The
Gaussian reduces the effect of noise present in the image. Then, potential
edges are thinned down to 1-pixel curves by removing non-maximum pixels of the
gradient magnitude. Finally, edge pixels are kept or removed using hysteresis
thresholding on the gradient magnitude.

The Canny has three adjustable parameters: the width of the Gaussian (the
noisier the image, the greater the width), and the low and high threshold for
the hysteresis thresholding.

.. GENERATED FROM PYTHON SOURCE LINES 18-56



.. image:: /auto_examples/edges/images/sphx_glr_plot_canny_001.png
    :alt: noisy image, Canny filter, $\sigma=1$, Canny filter, $\sigma=3$
    :class: sphx-glr-single-img





.. code-block:: default

    import numpy as np
    import matplotlib.pyplot as plt
    from scipy import ndimage as ndi

    from skimage import feature


    # Generate noisy image of a square
    im = np.zeros((128, 128))
    im[32:-32, 32:-32] = 1

    im = ndi.rotate(im, 15, mode='constant')
    im = ndi.gaussian_filter(im, 4)
    im += 0.2 * np.random.random(im.shape)

    # Compute the Canny filter for two values of sigma
    edges1 = feature.canny(im)
    edges2 = feature.canny(im, sigma=3)

    # display results
    fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3),
                                        sharex=True, sharey=True)

    ax1.imshow(im, cmap=plt.cm.gray)
    ax1.axis('off')
    ax1.set_title('noisy image', fontsize=20)

    ax2.imshow(edges1, cmap=plt.cm.gray)
    ax2.axis('off')
    ax2.set_title(r'Canny filter, $\sigma=1$', fontsize=20)

    ax3.imshow(edges2, cmap=plt.cm.gray)
    ax3.axis('off')
    ax3.set_title(r'Canny filter, $\sigma=3$', fontsize=20)

    fig.tight_layout()

    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.219 seconds)


.. _sphx_glr_download_auto_examples_edges_plot_canny.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_canny.py <plot_canny.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_canny.ipynb <plot_canny.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_
