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

    Click :ref:`here <sphx_glr_download_auto_examples_segmentation_plot_peak_local_max.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_segmentation_plot_peak_local_max.py:


====================
Finding local maxima
====================

The ``peak_local_max`` function returns the coordinates of local peaks (maxima)
in an image. A maximum filter is used for finding local maxima. This operation
dilates the original image and merges neighboring local maxima closer than the
size of the dilation. Locations where the original image is equal to the
dilated image are returned as local maxima.





.. code-block:: pytb

    Traceback (most recent call last):
      File "/build/skimage-Lp2Zl4/skimage-0.16.2/doc/examples/segmentation/plot_peak_local_max.py", line 1
        ====================
        ^
    SyntaxError: invalid syntax





.. code-block:: python

    ====================
    Finding local maxima
    ====================

    The ``peak_local_max`` function returns the coordinates of local peaks (maxima)
    in an image. A maximum filter is used for finding local maxima. This operation
    dilates the original image and merges neighboring local maxima closer than the
    size of the dilation. Locations where the original image is equal to the
    dilated image are returned as local maxima.

    """
    from scipy import ndimage as ndi
    import matplotlib.pyplot as plt
    from skimage.feature import peak_local_max
    from skimage import data, img_as_float

    im = img_as_float(data.coins())

    # image_max is the dilation of im with a 20*20 structuring element
    # It is used within peak_local_max function
    image_max = ndi.maximum_filter(im, size=20, mode='constant')

    # Comparison between image_max and im to find the coordinates of local maxima
    coordinates = peak_local_max(im, min_distance=20)

    # display results
    fig, axes = plt.subplots(1, 3, figsize=(8, 3), sharex=True, sharey=True)
    ax = axes.ravel()
    ax[0].imshow(im, cmap=plt.cm.gray)
    ax[0].axis('off')
    ax[0].set_title('Original')

    ax[1].imshow(image_max, cmap=plt.cm.gray)
    ax[1].axis('off')
    ax[1].set_title('Maximum filter')

    ax[2].imshow(im, cmap=plt.cm.gray)
    ax[2].autoscale(False)
    ax[2].plot(coordinates[:, 1], coordinates[:, 0], 'r.')
    ax[2].axis('off')
    ax[2].set_title('Peak local max')

    fig.tight_layout()

    plt.show()

**Total running time of the script:** ( 0 minutes  0.000 seconds)


.. _sphx_glr_download_auto_examples_segmentation_plot_peak_local_max.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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