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A Framework in C# for Fingerprint Verification

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>An implementation of the minutiae matching algorithm proposed by Qi et al. in 2005.  
 <a href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w.html#details">More...</a></p>
<div class="dynheader">
Inheritance diagram for PatternRecognition.FingerprintRecognition.Matchers.QYW:</div>
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 <div class="center">
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<area href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g.html" title="Provides a base class for implementations of the IMatcher&amp;lt;FeatureType&amp;gt; generic interface..." alt="PatternRecognition.FingerprintRecognition.Core.Matcher&lt; FeatureType &gt;" shape="rect" coords="0,56,454,80"/>
<area href="interface_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_i_minutia_matcher.html" title="Represents a minutia matching algorithm." alt="PatternRecognition.FingerprintRecognition.Core.IMinutiaMatcher" shape="rect" coords="464,56,918,80"/>
<area href="interface_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_i_matcher.html" alt="PatternRecognition.FingerprintRecognition.Core.IMatcher&lt; FeatureType &gt;" shape="rect" coords="0,0,454,24"/>
<area href="interface_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_i_matcher.html" title="Represents a non-generic fingerprint matching algorithm." alt="PatternRecognition.FingerprintRecognition.Core.IMatcher" shape="rect" coords="464,0,918,24"/>
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<p><a href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w-members.html">List of all members.</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2><a name="nested-classes"></a>
Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><b>FingerprintRegion</b></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><b>MtiaMapper</b></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><b>MtiaPairComparer</b></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><b>PolygonMapper</b></td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:ac387f90b923c9dabc0448a0f60e0299f"><td class="memItemLeft" align="right" valign="top">override double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w.html#ac387f90b923c9dabc0448a0f60e0299f">Match</a> (<a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_representation_1_1_qi2005_features.html">Qi2005Features</a> query, <a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_representation_1_1_qi2005_features.html">Qi2005Features</a> template)</td></tr>
<tr class="memdesc:ac387f90b923c9dabc0448a0f60e0299f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Matches the specified fingerprint features.  <a href="#ac387f90b923c9dabc0448a0f60e0299f"></a><br/></td></tr>
<tr class="memitem:a6658fbd30a6b23c41fe8f16747d7d7d8"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w.html#a6658fbd30a6b23c41fe8f16747d7d7d8">Match</a> (object query, object template, out List&lt; <a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_minutia_pair.html">MinutiaPair</a> &gt; matchingMtiae)</td></tr>
<tr class="memdesc:a6658fbd30a6b23c41fe8f16747d7d7d8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Matches the specified fingerprint features and outputs the matching minutiae.  <a href="#a6658fbd30a6b23c41fe8f16747d7d7d8"></a><br/></td></tr>
<tr class="inherit_header pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g')"><img src="closed.png" alt="-"/>&nbsp;Public Member Functions inherited from <a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g.html">PatternRecognition.FingerprintRecognition.Core.Matcher< FeatureType ></a></td></tr>
<tr class="memitem:a986c2844df5f5cd8abd00d7f4ae7798c inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g"><td class="memItemLeft" align="right" valign="top">abstract double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g.html#a986c2844df5f5cd8abd00d7f4ae7798c">Match</a> (FeatureType query, FeatureType template)</td></tr>
<tr class="memdesc:a986c2844df5f5cd8abd00d7f4ae7798c inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g"><td class="mdescLeft">&#160;</td><td class="mdescRight">When implemented in a derived class, matches the specified fingerprint features.  <a href="#a986c2844df5f5cd8abd00d7f4ae7798c"></a><br/></td></tr>
<tr class="memitem:aaeff90f259cae2d928842fd36a2fb3f5 inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g.html#aaeff90f259cae2d928842fd36a2fb3f5">Match</a> (object query, object template)</td></tr>
<tr class="memdesc:aaeff90f259cae2d928842fd36a2fb3f5 inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_matcher-g"><td class="mdescLeft">&#160;</td><td class="mdescRight">Matches the specified fingerprint features.  <a href="#aaeff90f259cae2d928842fd36a2fb3f5"></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:a73a21bc4a16763d24b6434f6ca4fb275"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w.html#a73a21bc4a16763d24b6434f6ca4fb275">GlobalDistThr</a><code> [get, set]</code></td></tr>
<tr class="memdesc:a73a21bc4a16763d24b6434f6ca4fb275"><td class="mdescLeft">&#160;</td><td class="mdescRight">Distance threshold for the global minutia matching step.  <a href="#a73a21bc4a16763d24b6434f6ca4fb275"></a><br/></td></tr>
<tr class="memitem:af8c41f269e806c6a494e18d2db2f838b"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_matchers_1_1_q_y_w.html#af8c41f269e806c6a494e18d2db2f838b">GlobalAngleThr</a><code> [get, set]</code></td></tr>
<tr class="memdesc:af8c41f269e806c6a494e18d2db2f838b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Angle threshold for the global minutia matching step.  <a href="#af8c41f269e806c6a494e18d2db2f838b"></a><br/></td></tr>
</table>
<hr/><a name="details" id="details"></a><h2>Detailed Description</h2>
<div class="textblock"><p>An implementation of the minutiae matching algorithm proposed by Qi et al. in 2005. </p>
<p>This is an implementation of the minutiae matching algorithm proposed by Qi et al. [1] in 2005. </p>
<p>Take into account that this algorithm is created to work with fingerprint images at 500 dpi. Proper modifications have to be made for different image resolutions. </p>
<p>References: </p>
<ol>
<li>
J. Qi, S. Yang, and Y. Wang, "Fingerprint matching combining the global orientation field with minutia," Pattern Recognition Letters, vol. 26, pp. 2424-2430, 2005.  </li>
</ol>
</div><hr/><h2>Member Function Documentation</h2>
<a class="anchor" id="ac387f90b923c9dabc0448a0f60e0299f"></a>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">override double PatternRecognition.FingerprintRecognition.Matchers.QYW.Match </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_representation_1_1_qi2005_features.html">Qi2005Features</a>&#160;</td>
          <td class="paramname"><em>query</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_representation_1_1_qi2005_features.html">Qi2005Features</a>&#160;</td>
          <td class="paramname"><em>template</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Matches the specified fingerprint features. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">query</td><td>The query fingerprint features. </td></tr>
    <tr><td class="paramname">template</td><td>The template fingerprint features. </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns:</dt><dd>The fingerprint similarity value. </dd></dl>

</div>
</div>
<a class="anchor" id="a6658fbd30a6b23c41fe8f16747d7d7d8"></a>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">double PatternRecognition.FingerprintRecognition.Matchers.QYW.Match </td>
          <td>(</td>
          <td class="paramtype">object&#160;</td>
          <td class="paramname"><em>query</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">object&#160;</td>
          <td class="paramname"><em>template</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">out List&lt; <a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_minutia_pair.html">MinutiaPair</a> &gt;&#160;</td>
          <td class="paramname"><em>matchingMtiae</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Matches the specified fingerprint features and outputs the matching minutiae. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">query</td><td>The query fingerprint features. </td></tr>
    <tr><td class="paramname">template</td><td>The template fingerprint features. </td></tr>
    <tr><td class="paramname">matchingMtiae</td><td>The matching minutiae. </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 features has invalid type.</td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns:</dt><dd>The fingerprint similarity value. </dd></dl>

<p>Implements <a class="el" href="interface_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_i_minutia_matcher.html#aac70bf6930eb9c111454ca8c04fb57ba">PatternRecognition.FingerprintRecognition.Core.IMinutiaMatcher</a>.</p>

</div>
</div>
<hr/><h2>Property Documentation</h2>
<a class="anchor" id="af8c41f269e806c6a494e18d2db2f838b"></a>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">double PatternRecognition.FingerprintRecognition.Matchers.QYW.GlobalAngleThr</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>Angle threshold for the global minutia matching step. </p>
<p>This threshold is used to compare angles in the global minutia matching step. For more information refer to the original paper. </p>

</div>
</div>
<a class="anchor" id="a73a21bc4a16763d24b6434f6ca4fb275"></a>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">int PatternRecognition.FingerprintRecognition.Matchers.QYW.GlobalDistThr</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>Distance threshold for the global minutia matching step. </p>
<p>This threshold is used to compare minutia distances in the global minutia matching step. For more information refer to the original paper. </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/FR.Qi2005/QYW.cs</li>
</ul>
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Written By
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
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.

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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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