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A Framework in C# for Fingerprint Verification

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2 Jan 2019CPOL11 min read 1.6M   143.6K   672  
In this article, we introduce a framework in C# for fingerprint verification, we briefly explain how to perform fingerprint verification experiments and how to integrate your algorithms to the framework.
 
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<p>Represents a convolution filter.  
 <a href="class_image_processing_tools_1_1_convolution_filter.html#details">More...</a></p>
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Inheritance diagram for ImageProcessingTools.ConvolutionFilter:</div>
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<p><a href="class_image_processing_tools_1_1_convolution_filter-members.html">List of all members.</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a07df919a825c2e56890227dbebd9a164"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a07df919a825c2e56890227dbebd9a164">ConvolutionFilter</a> (int width, int height, int factor)</td></tr>
<tr class="memdesc:a07df919a825c2e56890227dbebd9a164"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialize a <a class="el" href="class_image_processing_tools_1_1_convolution_filter.html" title="Represents a convolution filter.">ConvolutionFilter</a> with the specified width, height and factor.  <a href="#a07df919a825c2e56890227dbebd9a164"></a><br/></td></tr>
<tr class="memitem:a641af1adb7b280fcea011644cfdb2425"><td class="memItemLeft" align="right" valign="top"><a class="el" href="class_image_processing_tools_1_1_image_matrix.html">ImageMatrix</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a641af1adb7b280fcea011644cfdb2425">Apply</a> (<a class="el" href="class_image_processing_tools_1_1_image_matrix.html">ImageMatrix</a> img)</td></tr>
<tr class="memdesc:a641af1adb7b280fcea011644cfdb2425"><td class="mdescLeft">&#160;</td><td class="mdescRight">Applies the current convolution filter to the specified <a class="el" href="class_image_processing_tools_1_1_image_matrix.html" title="A class to represent a gray scale image using a matrix.">ImageMatrix</a>.  <a href="#a641af1adb7b280fcea011644cfdb2425"></a><br/></td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr class="memitem:a8e392d752ef8c64d945c6d32de670b51"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a8e392d752ef8c64d945c6d32de670b51">ConvolutionFilter</a> ()</td></tr>
<tr class="memdesc:a8e392d752ef8c64d945c6d32de670b51"><td class="mdescLeft">&#160;</td><td class="mdescRight">A base constructor to be used in concrete classes.  <a href="#a8e392d752ef8c64d945c6d32de670b51"></a><br/></td></tr>
</table><table class="memberdecls">
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Protected Attributes</h2></td></tr>
<tr class="memitem:a3f9a2a32bad42ed07b2a472c75cd1140"><td class="memItemLeft" align="right" valign="top">int[,]&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a3f9a2a32bad42ed07b2a472c75cd1140">pixels</a></td></tr>
<tr class="memdesc:a3f9a2a32bad42ed07b2a472c75cd1140"><td class="mdescLeft">&#160;</td><td class="mdescRight">The matrix of the filter.  <a href="#a3f9a2a32bad42ed07b2a472c75cd1140"></a><br/></td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2><a name="properties"></a>
Properties</h2></td></tr>
<tr class="memitem:a386e9e770b2ab3c3c2c072c1b1357e6f"><td class="memItemLeft" align="right" valign="top">virtual int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a386e9e770b2ab3c3c2c072c1b1357e6f">this[int row, int column]</a><code> [get, set]</code></td></tr>
<tr class="memdesc:a386e9e770b2ab3c3c2c072c1b1357e6f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Gets or sets the value of a pixel in the filter.  <a href="#a386e9e770b2ab3c3c2c072c1b1357e6f"></a><br/></td></tr>
<tr class="memitem:afd201a517a241fa1ec49ad050bb5b026"><td class="memItemLeft" align="right" valign="top">virtual int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#afd201a517a241fa1ec49ad050bb5b026">Height</a><code> [get, set]</code></td></tr>
<tr class="memdesc:afd201a517a241fa1ec49ad050bb5b026"><td class="mdescLeft">&#160;</td><td class="mdescRight">Gets the height of the filter.  <a href="#afd201a517a241fa1ec49ad050bb5b026"></a><br/></td></tr>
<tr class="memitem:a1e948c19acff5e1b85bbd2c4550c6308"><td class="memItemLeft" align="right" valign="top">virtual int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#a1e948c19acff5e1b85bbd2c4550c6308">Width</a><code> [get, set]</code></td></tr>
<tr class="memdesc:a1e948c19acff5e1b85bbd2c4550c6308"><td class="mdescLeft">&#160;</td><td class="mdescRight">Gets the width of the filter.  <a href="#a1e948c19acff5e1b85bbd2c4550c6308"></a><br/></td></tr>
<tr class="memitem:ad6dc280de472324bee0862cb2d2e518d"><td class="memItemLeft" align="right" valign="top">virtual int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_image_processing_tools_1_1_convolution_filter.html#ad6dc280de472324bee0862cb2d2e518d">Factor</a><code> [get, set]</code></td></tr>
<tr class="memdesc:ad6dc280de472324bee0862cb2d2e518d"><td class="mdescLeft">&#160;</td><td class="mdescRight">A factor to divide the value before assigning to the pixel.  <a href="#ad6dc280de472324bee0862cb2d2e518d"></a><br/></td></tr>
</table>
<hr/><a name="details" id="details"></a><h2>Detailed Description</h2>
<div class="textblock"><p>Represents a convolution filter. </p>
</div><hr/><h2>Constructor &amp; Destructor Documentation</h2>
<a class="anchor" id="a07df919a825c2e56890227dbebd9a164"></a>
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          <td class="memname">ImageProcessingTools.ConvolutionFilter.ConvolutionFilter </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>factor</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Initialize a <a class="el" href="class_image_processing_tools_1_1_convolution_filter.html" title="Represents a convolution filter.">ConvolutionFilter</a> with the specified width, height and factor. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">width</td><td>The width of the filter.</td></tr>
    <tr><td class="paramname">height</td><td>The height of the filter.</td></tr>
    <tr><td class="paramname">factor</td><td>The factor to divide the value before assigining to the pixel.</td></tr>
  </table>
  </dd>
</dl>
<dl class="exception"><dt>Exceptions:</dt><dd>
  <table class="exception">
    <tr><td class="paramname">ArgumentOutOfRangeException</td><td>Thrown when the specified with or height are not an odd number.</td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
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          <td class="memname">ImageProcessingTools.ConvolutionFilter.ConvolutionFilter </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
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<p>A base constructor to be used in concrete classes. </p>

</div>
</div>
<hr/><h2>Member Function Documentation</h2>
<a class="anchor" id="a641af1adb7b280fcea011644cfdb2425"></a>
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          <td class="memname"><a class="el" href="class_image_processing_tools_1_1_image_matrix.html">ImageMatrix</a> ImageProcessingTools.ConvolutionFilter.Apply </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="class_image_processing_tools_1_1_image_matrix.html">ImageMatrix</a>&#160;</td>
          <td class="paramname"><em>img</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Applies the current convolution filter to the specified <a class="el" href="class_image_processing_tools_1_1_image_matrix.html" title="A class to represent a gray scale image using a matrix.">ImageMatrix</a>. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">img</td><td>The <a class="el" href="class_image_processing_tools_1_1_image_matrix.html" title="A class to represent a gray scale image using a matrix.">ImageMatrix</a> where the convolution filter will be applied. </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns:</dt><dd>A new <a class="el" href="class_image_processing_tools_1_1_image_matrix.html" title="A class to represent a gray scale image using a matrix.">ImageMatrix</a> resulting from applying the current filter to the specified <a class="el" href="class_image_processing_tools_1_1_image_matrix.html" title="A class to represent a gray scale image using a matrix.">ImageMatrix</a>. </dd></dl>

</div>
</div>
<hr/><h2>Member Data Documentation</h2>
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          <td class="memname">int [,] ImageProcessingTools.ConvolutionFilter.pixels</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
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<p>The matrix of the filter. </p>

</div>
</div>
<hr/><h2>Property Documentation</h2>
<a class="anchor" id="ad6dc280de472324bee0862cb2d2e518d"></a>
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          <td class="memname">virtual int ImageProcessingTools.ConvolutionFilter.Factor</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">get</span><span class="mlabel">set</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>A factor to divide the value before assigning to the pixel. </p>

<p>Reimplemented in <a class="el" href="class_image_processing_tools_1_1_sobel_horizontal_filter.html#a99f77b26280f3540013c320d45b27445">ImageProcessingTools.SobelHorizontalFilter</a>, <a class="el" href="class_image_processing_tools_1_1_sobel_vertical_filter.html#a33d870fbf1f4e1fe82bedfa49756c7fe">ImageProcessingTools.SobelVerticalFilter</a>, and <a class="el" href="class_image_processing_tools_1_1_gaussian_blur.html#a1c05ecf1f6dbc0ceedd7dd74cc095fe8">ImageProcessingTools.GaussianBlur</a>.</p>

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      <table class="memname">
        <tr>
          <td class="memname">virtual int ImageProcessingTools.ConvolutionFilter.Height</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">get</span><span class="mlabel">set</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Gets the height of the filter. </p>

<p>Reimplemented in <a class="el" href="class_image_processing_tools_1_1_sobel_horizontal_filter.html#a5ebb24e3c2cfc8a0ad17ec996f76fa71">ImageProcessingTools.SobelHorizontalFilter</a>, <a class="el" href="class_image_processing_tools_1_1_sobel_vertical_filter.html#a784d7a0541da2af0485f930f33add9fe">ImageProcessingTools.SobelVerticalFilter</a>, and <a class="el" href="class_image_processing_tools_1_1_gaussian_blur.html#a08d864e55e6d7fb1ae45cd58675ae468">ImageProcessingTools.GaussianBlur</a>.</p>

</div>
</div>
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          <td class="memname">virtual int ImageProcessingTools.ConvolutionFilter.this[int row, int column]</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">get</span><span class="mlabel">set</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Gets or sets the value of a pixel in the filter. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">row</td><td>The row of the specified pixel.</td></tr>
    <tr><td class="paramname">column</td><td>The column of the specified pixel.</td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns:</dt><dd>The value of the filter in the specified pixel.</dd></dl>

</div>
</div>
<a class="anchor" id="a1e948c19acff5e1b85bbd2c4550c6308"></a>
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      <table class="memname">
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          <td class="memname">virtual int ImageProcessingTools.ConvolutionFilter.Width</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">get</span><span class="mlabel">set</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Gets the width of the filter. </p>

<p>Reimplemented in <a class="el" href="class_image_processing_tools_1_1_sobel_horizontal_filter.html#a3f092515d5fabd9515e2790125206ced">ImageProcessingTools.SobelHorizontalFilter</a>, <a class="el" href="class_image_processing_tools_1_1_sobel_vertical_filter.html#a018b1f45274df59685633002718d094a">ImageProcessingTools.SobelVerticalFilter</a>, and <a class="el" href="class_image_processing_tools_1_1_gaussian_blur.html#a3b6c792d6aaec74c9cf14b84c771eb7f">ImageProcessingTools.GaussianBlur</a>.</p>

</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>D:/Migue/Code/FingerprintRecognition/CodeProject/[2012-05-16] FingerprintRecognition/FingerprintRecognition/ImageProcessingTools/ConvolutionFilter.cs</li>
</ul>
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Written By
Miguel Angel Medina-Pérez
Tecnológico de Monterrey
Mexico Mexico
I received my B.S. and M.S. degrees from the University of Ciego de Ávila, Cuba, in 2007 and I received my PhD. degree in 2014 from the National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico.

I have developed software to solve pattern recognition problems. A successful example is the algorithm DMC which is the most accurate (according to EER) among those which compare both fingerprints and palmprints in the international competition FVC-onGoing.

I have been involved in several research projects about pattern recognition and I have published tens of papers in referenced journals such as "Pattern Recognition," "Knowledge-Based Systems," "Information Sciences", and "IEEE Transactions on Information Forensics and Security."

Written By
Milton García Borroto
Cuba Cuba
Milton García-Borroto is graduated from Las Villas Central University, Cuba, in 2000. He received the M.S. degree in 2007 from the National Institute of Astrophisics, Optics and Electronics, Mexico, where he continues his studies toward a Ph.D. degree. His research interests are pattern recognition and biometry.

Relevant papers:
1. M. García-Borroto, J. F. Martinez Trinidad, J. A. Carrasco Ochoa, M. A. Medina-Pérez, and J. Ruiz-Shulcloper. LCMine: An efficient algorithm for mining discriminative regularities and its application in supervised classification. Pattern Recognition vol. 43, pp. 3025-3034, 2010.
2. M. García-Borroto, J. F. Martinez Trinidad, J. A. Carrasco Ochoa. A New Emerging Pattern Mining Algorithm and Its Application in Supervised Classification. M.J. Zaki et al. (Eds.): PAKDD 2010, Part I, Lecture Notes in Artificial Intelligence, vol. 6118, pp. 150–157, 2010.
3. M. A. Medina-Pérez, A. Gutiérrez-Rodríguez, and M. García-Borroto, "Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor," Lecture Notes in Computer Science, vol. 5856, pp. 121-128, 2009.
4. M. García-Borroto, Y. Villuendas-Rey, J. A. Carrasco-Ochoa, and J. F. Martínez-Trinidad, "Finding Small Consistent Subset for the Nearest Neighbor Classifier Based on Support Graphs," Lecture Notes in Computer Science, vol. 5856, pp. 465-472, 2009.
5. M. García-Borroto, Y. Villuendas-Rey, J. A. Carrasco-Ochoa, and J. F. Martínez-Trinidad, "Using Maximum Similarity Graphs to Edit Nearest Neighbor Classifiers," Lecture Notes in Computer Science, vol. 5856, pp. 489-496, 2009.
6. M. A. Medina-Pérez, M. García-Borroto, and J. Ruiz-Shulcloper, "Object Selection Based on Subclass Error Correcting for ALVOT," Lecture Notes in Computer Science, vol. 4756, pp. 496-505, 2007.

Andres Eduardo Gutierrez Rodriguez is graduated from Las Villas Central University, Cuba, in 2006. He received the M.S. degree in 2009 from the University of Ciego de Ávila, Cuba. His research interests are pattern recognition and biometry.

Relevant papers:

-M. A. Medina-Pérez, A. Gutiérrez-Rodríguez, and M. García-Borroto, "Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor," Lecture Notes in Computer Science, vol. 5856, pp. 121-128, 2009.
-A. E. Gutierrez-Rodriguez, M. A. Medina-Perez, J. F. Martinez-Trinidad, J. A. Carrasco-Ochoa, and M. Garcia-Borroto, "New Dissimilarity Measures for Ultraviolet Spectra Identification," Lecture Notes in Computer Science, vol. 6256, pp. 220-229, 2010.

Written By
Octavio Loyola-González
Program Manager
Spain Spain
Octavio Loyola-González received his PhD degree in Computer Science from the National Institute for Astrophysics, Optics, and Electronics, Mexico. He has won several awards from different institutions due to his research work on applied projects; consequently, he is a Member of the National System of Researchers in Mexico (Rank1). He worked as a distinguished professor and researcher at Tecnologico de Monterrey, Campus Puebla, for undergraduate and graduate programs of Computer Sciences. Currently, he is responsible for running Machine Learning & Artificial Intelligence practice inside Stratesys., where he is involved in the development and implementation using analytics and data mining. He has outstanding experience in the fields of big data & pattern recognition, cloud computing, IoT, and analytical tools to apply them in sectors where he has worked for as Banking & Insurance, Retail, Oil&Gas, Agriculture, Cybersecurity, Biotechnology, and Dactyloscopy. From these applied projects, Dr. Loyola-González has published several books and papers in well-known journals, and he has several ongoing patents as manager and researcher in Stratesys.

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Posted 30 Jul 2010

Article Copyright 2010 by Miguel Angel Medina-Pérez, Milton García Borroto, Andres Eduardo Gutierrez Rodriguez, Octavio Loyola-González
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