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Source code changes of the file "help/en_US/thin.xml" between
sip-0.5.6.tar.gz and sip-0.12.1.tar.gz

About: SIP (Scilab Image Processing) toolbox to do imaging tasks such as filtering, blurring, edge detection, thresholding, histogram manipulation, segmentation, mathematical morphology, color image processing, etc.

thin.xml  (sip-0.5.6):thin.xml  (sip-0.12.1)
<?xml version="1.0" encoding="ISO-8859-1"?><refentry xmlns="http://docbook.org/n s/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.o rg/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://doc book.org/ns/docbook" version="5.0-subset Scilab" xml:lang="en" xml:id="thin"><in fo><pubdate>February 2004</pubdate></info><refnamediv><refname>thin</refname><re fpurpose>thinning by border deletion</refpurpose></refnamediv> <?xml version="1.0" encoding="ISO-8859-1"?><refentry xmlns="http://docbook.org/n s/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.o rg/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://doc book.org/ns/docbook" version="5.0-subset Scilab" xml:lang="en" xml:id="thin"><in fo><pubdate>February 2004</pubdate></info><refnamediv><refname>thin</refname><re fpurpose>thinning by border deletion</refpurpose></refnamediv>
<refsynopsisdiv><title>Calling Sequence</title><synopsis>out = thin(img)</syn opsis></refsynopsisdiv> <refsynopsisdiv><title>Calling Sequence</title><synopsis>out = thin(img)</syn opsis></refsynopsisdiv>
<refsection><title>Parameters</title> <refsection><title>Parameters</title>
<variablelist> <variablelist>
<varlistentry> <varlistentry>
<term>img</term> <term>img</term>
<listitem> <listitem>
Binary image containing one or more binary shapes. (foreground == 1, back ground == 0), Binary image containing one or more binary shapes. (foreground == 1, back ground == 0),
</listitem> </listitem>
</varlistentry> </varlistentry>
<varlistentry> <varlistentry>
<term>out</term> <term>out</term>
<listitem> <listitem>
Internal skeleton, thinned version of the shapes in the input image. Internal skeleton, thinned version of the shapes in the input image.
</listitem> </listitem>
</varlistentry> </varlistentry>
</variablelist> </variablelist>
</refsection> </refsection>
<refsection><title>Description</title> <refsection><title>Description</title>
<para> <para>
Function <literal>thin</literal> performs thinning of binary objects. It uses the Zhang-Suen, a de facto standard and simple technique. The resulting ima ge, the skeleton, is not always connected and is very sensible to noise. It is also slower than a good skeletonization algorithm (see skel). For thin shapes, it should work faster and provide better quality. You will need some pruning c riterium to eliminate spurs. </para> Function <literal>thin</literal> performs thinning of binary objects. It uses the Zhang-Suen, a de facto standard and simple technique. The resulting ima ge, the skeleton, is not always connected and is very sensible to noise. It is also slower than a good skeletonization algorithm (see skel). For thin shapes, it should work faster and provide better quality. You will need some pruning c riterium to eliminate spurs. </para>
</refsection> </refsection>
<refsection><title>Examples</title><programlisting role="example"><![CDATA[ <refsection><title>Examples</title><programlisting role="example"><![CDATA[
im=gray_imread(SIPDIR+'images/r.gif'); im=gray_imread(SIPDIR+'images/r.gif');
imshow(im,2); imshow(im,2);
skl = thin(im); skl = thin(im);
clf; clf;
imshow(im+skl,[]); imshow(im+skl,[]);
// Quality is definitely inferior to that of good skeletonization // Quality is definitely inferior to that of good skeletonization
// methods, as in the following test // methods, as in the following test
im=gray_imread(SIPDIR+'images/escher.png'); im=gray_imread(SIPDIR+'images/escher.png');
skl = thin(im); // Ordinary thinning skl = thin(im); // Ordinary thinning
clf; clf;
xset('wdim',400,500); xset('wdim',400,500);
subplot(1,2,1); subplot(1,2,1);
imshow(im+skl,[]); imshow(im+skl,[]);
xset('wdim',800,400); xset('wdim',800,400);
skl = skel(im); // multiscale euclidean skeletonization skl = skel(im); // multiscale euclidean skeletonization
subplot(1,2,2); subplot(1,2,2);
imshow(im+(skl &gt;= 10),[]); imshow(im+(skl &gt;= 10),[]);
xset('wdim',800,400); xset('wdim',800,400);
]]></programlisting></refsection> ]]></programlisting></refsection>
<refsection><title>Authors</title><simplelist type="vert"> <refsection><title>Authors</title><simplelist type="vert">
<member> Ricardo Fabbri &lt;ricardofabbri (AT) users DOT sf DOT net&gt; </ member> <member> Ricardo Fabbri &lt;ricardofabbri (AT) users DOT sf DOT net&gt; </ member>
</simplelist></refsection> </simplelist></refsection>
<refsection><title>Availability</title> <refsection><title>Availability</title>
The latest version of the Scilab Image Processing toolbox can be found at The latest version of the Scilab Image Processing toolbox can be found at
<para> <para>
http://siptoolbox.sourceforge.net http://siptoolbox.sourceforge.net
</para> </para>
</refsection> </refsection>
<refsection><title>See Also</title><simplelist type="inline"> <refsection><title>See Also</title><simplelist type="inline">
<member> <member>
<link linkend="skel">skel</link> <link linkend="skel">skel</link>
</member> </member>
</simplelist></refsection> </simplelist></refsection>
</refentry> </refentry>
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