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<!--
 * Scilab Computer Vision Module
 * Copyright (C) 2017 - Scilab Enterprises
 *
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<refentry xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg"  xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" version="5.0-subset Scilab"
  xml:lang="fr" xml:id="HoughLines">
  <info>
    <pubdate>$LastChangedDate$</pubdate>
  </info>
  <refnamediv>
    <refname>HoughLines</refname>
    <refpurpose>Finds lines in a binary image using the standard Hough transform</refpurpose>
  </refnamediv>
  <refsynopsisdiv>
    <title>Syntax</title>
    <synopsis>lines = HoughLines(img, distance_res, angle_res, threshold)</synopsis>
  </refsynopsisdiv>
  <refsection>
    <title>Parameters</title>
    <variablelist>
      <varlistentry>
        <term>img</term>
        <listitem>
          <para>Image (<link linkend="Mat">Mat</link> 8-bit single channel).</para>
        </listitem>
      </varlistentry>
      <varlistentry>
        <term>distance_res</term>
        <listitem>
          <para>Distance resolution, in pixels (double).</para>
        </listitem>
      </varlistentry>
      <varlistentry>
        <term>angle_res</term>
        <listitem>
          <para>Angle resolution, in radians (double).</para>
        </listitem>
      </varlistentry>
      <varlistentry>
        <term>threshold</term>
        <listitem>
          <para>Threshold parameter (double).</para>
        </listitem>
      </varlistentry>
      <varlistentry>
        <term>lines</term>
        <listitem>
          <para>Output matrix of lines. Each column represents a line, coded in polar coordinates system (<literal>rho</literal>, <literal>theta</literal>). (double 2xn).</para>
        </listitem>
      </varlistentry>
    </variablelist>
  </refsection>
  <refsection>
    <title>Description</title>
    <para><function>HoughLines</function> find the lines in an image using the standard Hough transform. To apply, first an edge detection pre-processing is necessary.
    It keeps track of the intersection between curves of every point in the image. If the number of intersections is above the value of <term>threshold</term>, then the line is output in polar coordinates (<literal>rho, theta</literal>).</para>
  </refsection>
  <refsection>
    <title>Examples</title>
    <programlisting role="example"><![CDATA[
    scicv_Init();

    img_gray = imread(getSampleImage("shapes.png"), CV_LOAD_IMAGE_GRAYSCALE);

    thresh = 100;
    img_canny = Canny(img_gray, thresh, thresh*2, 3);

    lines = HoughLines(img_canny, 1, %pi/180, 50);

    rho = lines(1,:);
    theta = lines(2,:);
    a = cos(theta);
    b = sin(theta);
    xy0 = [rho; rho] .* [a; b];
    xy1 = xy0 - 1000 * [-b; a];
    xy2 = xy0 + 1000 * [-b; a];

    img_out = new_Mat(size(img_gray, 'r'), size(img_gray, 'c'), CV_8UC3);
    nb_lines = size(lines, 'c');
    for i=1:nb_lines
        line(img_out, xy1(:,i), xy2(:,i), [0,0,255]);
    end

    matplot(img_out);

    delete_Mat(img_gray);
    delete_Mat(img_canny);
    delete_Mat(img_out);
 ]]></programlisting>
  </refsection>
  <refsection>
    <title>See also</title>
    <simplelist type="inline">
      <member><link linkend="HoughLinesP">HoughLinesP</link></member>
    </simplelist>
  </refsection>
</refentry>
