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<td class="title">Demonstrations</td>
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<h1>mmdbeef
<br>
<span class="subtitle">Detect the lean meat region in a beef steak image.
</span>
</h1>
<div class="descr">
<H2>Description</H2>
<div class="H2">
<p>
Beucher's paradigm is applied for delineating sharply the lean meat region in the beef steak image. An internal and an external marker are necessary for the filtering step of the paradigm. In this step, small regions that does not have meat are eliminated.
</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 gray-scale image of the beef steak is read.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> a = mmreadgray('beef.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="320" src="../images/img_mmdbeef_001.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_001.jpg">a</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Filtering</H3>
<div class="H3">
<p>
<p>
The input image is simplified by the application of a a small closing. The dark area (inner lean part) is closed from the fat white area.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> b=mmclose(a,mmsedisk(2));</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="320" src="../images/img_mmdbeef_002.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_002.jpg">b</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>External marker 1/2</H3>
<div class="H3">
<p>
<p>
The external marker is built from the detection of the complete beef region and the extraction of its internal edge. As the beef is dark, it is detected by a low value threshold. After this threshold, small residual regions are eliminated by the binary areaclose operator.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> c = mmthreshad(a,uint8(10));</pre>
<pre class="computer"></pre>
<pre class="user">>>> d = mmareaclose(c,200);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(d);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="320" src="../images/img_mmdbeef_003.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_003.jpg">d</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>External marker 2/2</H3>
<div class="H3">
<p>
<p>
The internal edge generated is 13 points thick. It is created by the residues of an erosion by a large structuring element.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> e = mmgradm(d,mmsecross(1),mmsebox(13));</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="320" src="../images/img_mmdbeef_004.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_004.jpg">e</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Internal marker</H3>
<div class="H3">
<p>
<p>
The internal marker is a severe erosion of the steak. Both markers are combined by union and displayed as overlay on the gradient image
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> f= mmero(d,mmsecross(80));</pre>
<pre class="computer"></pre>
<pre class="user">>>> g = mmunion(e,f); </pre>
<pre class="computer"></pre>
<pre class="user">>>> h = mmgradm(b);</pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(h,g);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="320" src="../images/img_mmdbeef_005.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_005.jpg">h,g</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Watershed</H3>
<div class="H3">
<p>
<p>
Constrained watershed of the gradient of the smoothed image, restricted to the internal and external markers
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> i=mmcwatershed(h,g); </pre>
<pre class="computer"></pre>
<pre class="user">>>> mmshow(i);</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="320" src="../images/img_mmdbeef_006.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_006.jpg">i</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
<div class="slide">
<H3>Final result</H3>
<div class="H3">
<p>
<p>
Superposition of the dilated detected contour on the original image.
</p>
<div class="example">
<div class="listing">
<pre class="user">>>> mmshow(a,mmdil(i));</pre>
<pre class="computer"></pre>
</div>
<table class="images">
<tbody align="center">
<tr class="image" valign="bottom">
<td><img width="320" src="../images/img_mmdbeef_007.jpg"></td>
<td class="spare"></td>
</tr>
<tr class="title" valign="baseline">
<td><a href="../images/img_mmdbeef_007.jpg">a,mmdil(i)</a></td>
<td class="spare"></td>
</tr>
</tbody>
</table>
</div>
</p>
</div>
</div>
</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
>
612
