Repository for OpenCV's extra modules
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.. ximgproc:
Structured forests for fast edge detection
******************************************
Introduction
------------
In this tutorial you will learn how to use structured forests for the purpose of edge detection in an image.
Examples
--------
.. image:: images/01.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/02.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/03.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/04.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/05.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/06.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/07.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/08.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/09.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/10.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/11.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
.. image:: images/12.jpg
:height: 238pt
:width: 750pt
:alt: First example
:align: center
**Note :** binarization techniques like Canny edge detector are applicable
to edges produced by both algorithms (``Sobel`` and ``StructuredEdgeDetection::detectEdges``).
Source Code
-----------
.. literalinclude:: ../../../../modules/ximpgroc/samples/cpp/structured_edge_detection.cpp
:language: cpp
:linenos:
:tab-width: 4
Explanation
-----------
1. **Load source color image**
.. code-block:: cpp
cv::Mat image = cv::imread(inFilename, 1);
if ( image.empty() )
{
printf("Cannot read image file: %s\n", inFilename.c_str());
return -1;
}
2. **Convert source image to [0;1] range**
.. code-block:: cpp
image.convertTo(image, cv::DataType<float>::type, 1/255.0);
3. **Run main algorithm**
.. code-block:: cpp
cv::Mat edges(image.size(), image.type());
cv::Ptr<StructuredEdgeDetection> pDollar =
cv::createStructuredEdgeDetection(modelFilename);
pDollar->detectEdges(image, edges);
4. **Show results**
.. code-block:: cpp
if ( outFilename == "" )
{
cv::namedWindow("edges", 1);
cv::imshow("edges", edges);
cv::waitKey(0);
}
else
cv::imwrite(outFilename, 255*edges);
Literature
----------
For more information, refer to the following papers :
.. [Dollar2013] Dollar P., Zitnick C. L., "Structured forests for fast edge detection",
IEEE International Conference on Computer Vision (ICCV), 2013,
pp. 1841-1848. `DOI <http://dx.doi.org/10.1109/ICCV.2013.231>`_
.. [Lim2013] Lim J. J., Zitnick C. L., Dollar P., "Sketch Tokens: A Learned
Mid-level Representation for Contour and Object Detection",
Comoputer Vision and Pattern Recognition (CVPR), 2013,
pp. 3158-3165. `DOI <http://dx.doi.org/10.1109/CVPR.2013.406>`_