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<td class="title">Demonstrations</td>
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<h1>mmdpieces
<br>
<span class="subtitle">Classify two dimensional pieces.
</span>
</h1>
<div class="descr">
<H2>Description</H2>
<div class="H2">
<p>
The input image is a binary image typically found in industrial automation applications. It has three types of objects: rings, nails and T-pins. Our procedure for identification of these classes of objects is based on thickening, thinning and reconstruction.
</p>
</div>
</div>
<div class="script">
<H2>Demo Script</H2>
<div class="H2">
<div class="slide">
<H3>Reading</H3>
<div class="H3">
<p>
<p>
The binary image of the pieces is read.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> a = mmreadgray('pieces_bw.tif');</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(a);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_001.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_001.jpg">a</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Contour noise reduction</H3>
<div class="H3">
<p>
<p>
An homotopic thickening is applied to reduce contour noise.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> seA = mmimg2se(mmbinary([[0,1,0],[1,0,1],[0,0,0]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> seB = mmimg2se(mmbinary([[0,0,0],[0,1,0],[0,0,0]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> iAB = mmse2hmt(seA,seB);</pre>
<pre class="computer"></pre>
<pre class="user">>>> print mmintershow(iAB)</pre>
<pre class="computer">. 1 .
1 0 1
. . .</pre>
<pre class="user">>>> b = mmthick(a, iAB);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(b);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_002.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_002.jpg">b</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Skeleton</H3>
<div class="H3">
<p>
<p>
The homotopic skeleton by thinning is created.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> c = mmthin(b);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(c);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_003.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_003.jpg">c</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Skeleton pruning</H3>
<div class="H3">
<p>
<p>
The open lines of the skeleton are pruned by the end point thinning. The remaining skeleton components will be loops, identifying the rings.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> d = mmthin(c,mmendpoints());</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(c,d);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_004.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_004.jpg">c,d</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Detect rings</H3>
<div class="H3">
<p>
<p>
Extraction of the rings by reconstruction of the thicked image from the filtered skeleton.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> e = mminfrec(d,b);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(e);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_005.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_005.jpg">e</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Rings in the input image</H3>
<div class="H3">
<p>
<p>
Restriction of the objects detected to the input-image.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> f = mmintersec(a,e);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(f);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_006.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_006.jpg">f</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Skeleton of the remaining objects</H3>
<div class="H3">
<p>
<p>
It eliminates the skeleton of the rings.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> g = mmsubm(c,e);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(g);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_007.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_007.jpg">g</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>End points filtering</H3>
<div class="H3">
<p>
<p>
It removes sucessively 4 end-points to let T junctions just on T-pins.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> h = mmthin(g, mmendpoints(), 4);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(h);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_008.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_008.jpg">h</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>T-pins markers</H3>
<div class="H3">
<p>
<p>
It detects triple points, applying the union of matchings with two templates. These points will identify (mark) the T-pins.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> seA1 = mmimg2se(mmbinary([[0,1,0],[0,1,0],[1,0,1]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> seB1 = mmimg2se(mmbinary([[0,0,0],[1,0,1],[0,1,0]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> seA2 = mmimg2se(mmbinary([[0,1,0],[1,1,1],[0,0,0]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> seB2 = mmimg2se(mmbinary([[1,0,1],[0,0,0],[0,1,0]]))</pre>
<pre class="computer"></pre>
<pre class="user">>>> i1 = mmsupcanon(h, mmse2hmt(seA1,seB1));</pre>
<pre class="computer"></pre>
<pre class="user">>>> i2 = mmsupcanon(h, mmse2hmt(seA2,seB2));</pre>
<pre class="computer"></pre>
<pre class="user">>>> i = mmunion(i1,i2);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(h,mmdil(i,mmsedisk(2)));</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_009.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_009.jpg">h,mmdil(i,mmsedisk(2))</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Detect T-pins</H3>
<div class="H3">
<p>
<p>
Detection of the T-pins by reconstruction of the ticked image from the T-pin markers.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> j = mminfrec(i,b,mmsebox());</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(j);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_010.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_010.jpg">j</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>T-pins in the input image</H3>
<div class="H3">
<p>
<p>
Restriction of the objects detect to the input image
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> k = mmintersec(a,j);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(k);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_011.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_011.jpg">k</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Detect nails</H3>
<div class="H3">
<p>
<p>
The nails are imediatly detected by the subtration of the images of the rings and T-pints from the input image.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> l = mmsubm(mmsubm(a,f),k);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(l);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_012.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_012.jpg">l</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Color composition</H3>
<div class="H3">
<p>
<p>
The result of the classification is presented in a pseudo color image.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> m = mmgray(f,'uint8',1);</pre>
<pre class="computer"></pre>
<pre class="user">>>> n = mmgray(k,'uint8',2);</pre>
<pre class="computer"></pre>
<pre class="user">>>> o = mmgray(l,'uint8',3);</pre>
<pre class="computer"></pre>
<pre class="user">>>> p = mmunion(m,n,o);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmlblshow(p);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="229" src="../images/img_mmdpieces_013.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdpieces_013.jpg">p</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
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<td class="copyright">Copyright (c) 2003, Roberto A. Lotufo, UNICAMP-University of Campinas; Rubens C. Machado, CenPRA-Renato Archer Research Center.</td>
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distrib
>
Mandriva
>
2010.0
>
i586
>
media
>
contrib-release
>
by-pkgid
>
4a71d9984febeb5a206904a5a379841a
>
files
>
631
