.. 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

        :ref:`Go to the end <sphx_glr_download_auto_examples_edges_plot_canny.py>`
        to download the full example code. or to run this example in your browser via Binder

.. 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 18-55



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





.. code-block:: Python


    import numpy as np
    import matplotlib.pyplot as plt
    from scipy import ndimage as ndi
    from skimage.util import random_noise
    from skimage import feature


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

    image = ndi.rotate(image, 15, mode='constant')
    image = ndi.gaussian_filter(image, 4)
    image = random_noise(image, mode='speckle', mean=0.1)

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

    # display results
    fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(8, 3))

    ax[0].imshow(image, cmap='gray')
    ax[0].set_title('noisy image', fontsize=20)

    ax[1].imshow(edges1, cmap='gray')
    ax[1].set_title(r'Canny filter, $\sigma=1$', fontsize=20)

    ax[2].imshow(edges2, cmap='gray')
    ax[2].set_title(r'Canny filter, $\sigma=3$', fontsize=20)

    for a in ax:
        a.axis('off')

    fig.tight_layout()
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.089 seconds)


.. _sphx_glr_download_auto_examples_edges_plot_canny.py:

.. only:: html

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

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/scikit-image/scikit-image/v0.24.0?filepath=notebooks/auto_examples/edges/plot_canny.ipynb
        :alt: Launch binder
        :width: 150 px

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

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

    .. 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-zip

      :download:`Download zipped: plot_canny.zip <plot_canny.zip>`


.. only:: html

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

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