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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_color_exposure_plot_rgb_to_hsv.py:


==========
RGB to HSV
==========

This example illustrates how RGB to HSV (Hue, Saturation, Value) conversion
[1]_ can be used to facilitate segmentation processes.

Usually, objects in images have distinct colors (hues) and luminosities, so
that these features can be used to separate different areas of the image.
In the RGB representation the hue and the luminosity are expressed as a linear
combination of the R,G,B channels, whereas they correspond to single channels
of the HSV image (the Hue and the Value channels). A simple segmentation of the
image can then be effectively performed by a mere thresholding of the HSV
channels.

.. [1] https://en.wikipedia.org/wiki/HSL_and_HSV

.. GENERATED FROM PYTHON SOURCE LINES 20-27

.. code-block:: default



    import matplotlib.pyplot as plt

    from skimage import data
    from skimage.color import rgb2hsv








.. GENERATED FROM PYTHON SOURCE LINES 28-29

We first load the RGB image and extract the Hue and Value channels:

.. GENERATED FROM PYTHON SOURCE LINES 29-49

.. code-block:: default


    rgb_img = data.coffee()
    hsv_img = rgb2hsv(rgb_img)
    hue_img = hsv_img[:, :, 0]
    value_img = hsv_img[:, :, 2]

    fig, (ax0, ax1, ax2) = plt.subplots(ncols=3, figsize=(8, 2))

    ax0.imshow(rgb_img)
    ax0.set_title("RGB image")
    ax0.axis('off')
    ax1.imshow(hue_img, cmap='hsv')
    ax1.set_title("Hue channel")
    ax1.axis('off')
    ax2.imshow(value_img)
    ax2.set_title("Value channel")
    ax2.axis('off')

    fig.tight_layout()




.. image:: /auto_examples/color_exposure/images/sphx_glr_plot_rgb_to_hsv_001.png
    :alt: RGB image, Hue channel, Value channel
    :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 50-52

We then set a threshold on the Hue channel to separate the cup from the
background:

.. GENERATED FROM PYTHON SOURCE LINES 52-68

.. code-block:: default


    hue_threshold = 0.04
    binary_img = hue_img > hue_threshold

    fig, (ax0, ax1) = plt.subplots(ncols=2, figsize=(8, 3))

    ax0.hist(hue_img.ravel(), 512)
    ax0.set_title("Histogram of the Hue channel with threshold")
    ax0.axvline(x=hue_threshold, color='r', linestyle='dashed', linewidth=2)
    ax0.set_xbound(0, 0.12)
    ax1.imshow(binary_img)
    ax1.set_title("Hue-thresholded image")
    ax1.axis('off')

    fig.tight_layout()




.. image:: /auto_examples/color_exposure/images/sphx_glr_plot_rgb_to_hsv_002.png
    :alt: Histogram of the Hue channel with threshold, Hue-thresholded image
    :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 69-71

We finally perform an additional thresholding on the Value channel to partly
remove the shadow of the cup:

.. GENERATED FROM PYTHON SOURCE LINES 71-83

.. code-block:: default


    fig, ax0 = plt.subplots(figsize=(4, 3))

    value_threshold = 0.10
    binary_img = (hue_img > hue_threshold) | (value_img < value_threshold)

    ax0.imshow(binary_img)
    ax0.set_title("Hue and value thresholded image")
    ax0.axis('off')

    fig.tight_layout()
    plt.show()



.. image:: /auto_examples/color_exposure/images/sphx_glr_plot_rgb_to_hsv_003.png
    :alt: Hue and value thresholded image
    :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  0.651 seconds)


.. _sphx_glr_download_auto_examples_color_exposure_plot_rgb_to_hsv.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_rgb_to_hsv.py <plot_rgb_to_hsv.py>`



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

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


.. only:: html

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

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