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Mon Jan 28 00:22:09 CET 2008

must be the most important factor here...

I will make a small test program to compare...

Gilles

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<div>2008/1/28, Marcel Wiesweg &lt;<a href="mailto:marcel.wiesweg at gmx.de">marcel.wiesweg at gmx.de</a>&gt;:<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
&gt; * New features : &gt;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;- Added functions &#39;CImg&lt;T&gt;::get_haar()&#39;, &#39;CImg&lt;T&gt;::haar()&#39; allowing to &gt; compute the direct and &gt;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;inverse Haar multiscale transform on 2D or 3D images. 
&gt; &gt; Like you know, we will store and use Haar matrix into database to perform &gt; image fuzzy searches and duplicate items). &gt; &gt; What do you think to use this way to compute Haar matrix ? &gt; 
&gt; Alternative way is to import Haar algorithm from ImgSeek : &gt; &gt; <a href="http://imgseek.svn.sourceforge.net/viewvc/imgseek/trunk/imgseek-python/imgS">http://imgseek.svn.sourceforge.net/viewvc/imgseek/trunk/imgseek-python/imgS</a> 
&gt;eekLib/haar.cpp?revision=56&amp;view=markup &gt; <a href="http://imgseek.svn.sourceforge.net/viewvc/imgseek/trunk/imgseek-python/imgS">http://imgseek.svn.sourceforge.net/viewvc/imgseek/trunk/imgseek-python/imgS</a> 
&gt;eekLib/haar.h?revision=56&amp;view=markup &gt; &gt; ... But this can be more complicated to do... &gt; &gt; Your viewpoints ? If there are no strong reasons not to use CImg in this case (very slow), which 
I dont believe - in ImgSeek it was written in Python with native code parts after all - then it comes just right in time to save us some time, doesnt it?</blockquote><div> From ImgSeek, there is only haar algorithm witch have been written in C++ like you can see. 
 From CImg, i don&#39;t know if algorithm speed-up. And, you have right, speed must be the most important factor here... I will make a small test program to compare... Gilles</div></div>

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