<p>Symbol spotting is more complicated than logo spotting because interest points work hardly on document images such as architectural plans. Many conferences deals with pattern recognition, each year there are many new algorithms for symbol spotting so giving you the best method is not possible. You could check IAPR conferences : ICPR, ICDAR, DAS, GREC (Workshop on Graphics Recognition), etc. This researchers focus on this topic : M Rusiñol, J Lladós, S Tabbone, J-Y Ramel, M Liwicki, etc. They work on several techniques for improving symbol spotting such as : <a href="http://www.cvc.uab.es/~marcal/pdfs/GREC06.pdf" rel="nofollow">vectorial signatures</a>, <a href="http://arxiv.org/pdf/1004.5424" rel="nofollow">graph based signature</a> and so on (check google scholar for more papers).</p>

<p>An easy way to start a new approach is to work with simples shapes such as lines, rectangles, triangles instead of matching everything at one time.</p>
What is the best method to template match a image with noise?
<p>I have a large image (5400x3600) that has multiple CCTVs that I need to detect.</p>
<p>The detection takes lot of time (4-7 minutes) with rotation. But it still fails to resolve certain CCTVs.</p>
<p>What is the best method to match a template like this?</p>
<p>I am using skImage - openCV is not an option for me, but I am open to suggestions on that too.</p>
<p>For example: in the images below, the template is correct matched with the second image - but the first image is not matched - I guess due to the noise created by the text &quot;BLDG...&quot;</p>
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<h2>Template:</h2>
<p><img src="https://i.stack.imgur.com/p6zav.png" alt="Template" /></p>
<hr />
<h2>Source image:</h2>
<p><img src="https://i.stack.imgur.com/06XME.png" alt="Source image" /></p>
<hr />
<h2>Match result:</h2>
<p><img src="https://i.stack.imgur.com/T5rXi.png" alt="Match result" /></p>