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	<title>2024Almira TTM - Revision history</title>
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	<updated>2026-05-01T10:09:08Z</updated>
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		<id>https://3demmethods.i2pc.es/index.php?title=2024Almira_TTM&amp;diff=4935&amp;oldid=prev</id>
		<title>WikiSysop: Created page with &quot;== Citation ==  J. M. Almira, H. Phelippeau, and A. Martinez-Sanchez, “Fast normalized cross-correlation for template matching with rotations,” Journal of Applied Mathematics and Computing, vol. 70, no. 5, pp. 4937–4969, 2024.  == Abstract ==  Normalized cross-correlation is the reference approach to carry out template matching on images. When it is computed in Fourier space, it can handle efficiently template translations but it cannot do so with template rotation...&quot;</title>
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		<updated>2025-02-04T06:33:43Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  J. M. Almira, H. Phelippeau, and A. Martinez-Sanchez, “Fast normalized cross-correlation for template matching with rotations,” Journal of Applied Mathematics and Computing, vol. 70, no. 5, pp. 4937–4969, 2024.  == Abstract ==  Normalized cross-correlation is the reference approach to carry out template matching on images. When it is computed in Fourier space, it can handle efficiently template translations but it cannot do so with template rotation...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
&lt;br /&gt;
J. M. Almira, H. Phelippeau, and A. Martinez-Sanchez, “Fast normalized cross-correlation for template matching with rotations,” Journal of Applied Mathematics and Computing, vol. 70, no. 5, pp. 4937–4969, 2024.&lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
Normalized cross-correlation is the reference approach to carry out template matching&lt;br /&gt;
on images. When it is computed in Fourier space, it can handle efficiently template&lt;br /&gt;
translations but it cannot do so with template rotations. Including rotations requires&lt;br /&gt;
sampling the whole space of rotations, repeating the computation of the correlation&lt;br /&gt;
each time. This article develops an alternative mathematical theory to handle efficiently,&lt;br /&gt;
at the same time, rotations and translations. Our proposal has a reduced computational&lt;br /&gt;
complexity because it does not require to repeatedly sample the space of rotations.&lt;br /&gt;
To do so, we integrate the information relative to all rotated versions of the template&lt;br /&gt;
into a unique symmetric tensor template -which is computed only once per template-.&lt;br /&gt;
Afterward, we demonstrate that the correlation between the image to be processed&lt;br /&gt;
with the independent tensor components of the tensorial template contains enough&lt;br /&gt;
information to recover template instance positions and rotations.Our proposed method&lt;br /&gt;
has the potential to speed up conventional template matching computations by a factor&lt;br /&gt;
of several magnitude orders for the case of 3D images.&lt;br /&gt;
&lt;br /&gt;
== Keywords ==&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
&lt;br /&gt;
https://link.springer.com/article/10.1007/s12190-024-02157-6&lt;br /&gt;
&lt;br /&gt;
== Related software ==&lt;br /&gt;
&lt;br /&gt;
== Related methods ==&lt;br /&gt;
&lt;br /&gt;
== Comments ==&lt;/div&gt;</summary>
		<author><name>WikiSysop</name></author>
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