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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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<div class="title">PatternRecognition.FingerprintRecognition.FeatureDisplay.SkeletonImageDisplay Class Reference</div>  </div>
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<p>Used to paint skeleton image.  
 <a href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_display_1_1_skeleton_image_display.html#details">More...</a></p>
<div class="dynheader">
Inheritance diagram for PatternRecognition.FingerprintRecognition.FeatureDisplay.SkeletonImageDisplay:</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_feature_display-g.html" title="Provides a base class for implementations of the IFeatureDisplay&amp;lt;FeatureType&amp;gt; generic interface..." alt="PatternRecognition.FingerprintRecognition.Core.FeatureDisplay&lt; FeatureType &gt;" shape="rect" coords="0,56,483,80"/>
<area href="interface_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_i_feature_display.html" alt="PatternRecognition.FingerprintRecognition.Core.IFeatureDisplay&lt; FeatureType &gt;" shape="rect" coords="0,0,483,24"/>
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<p><a href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_display_1_1_skeleton_image_display-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:a323c276ed8668042752709d37c4fd0e1"><td class="memItemLeft" align="right" valign="top">override void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_display_1_1_skeleton_image_display.html#a323c276ed8668042752709d37c4fd0e1">Show</a> (<a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_skeleton_image.html">SkeletonImage</a> skImg, Graphics g)</td></tr>
<tr class="memdesc:a323c276ed8668042752709d37c4fd0e1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Paints the specified SkeletonImage using the specified Graphics.  <a href="#a323c276ed8668042752709d37c4fd0e1"></a><br/></td></tr>
<tr class="inherit_header pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-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_feature_display-g.html">PatternRecognition.FingerprintRecognition.Core.FeatureDisplay< FeatureType ></a></td></tr>
<tr class="memitem:ac7e5fc50598a5f7e9d6115b38e5c962f inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g"><td class="memItemLeft" align="right" valign="top">abstract void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g.html#ac7e5fc50598a5f7e9d6115b38e5c962f">Show</a> (FeatureType features, Graphics g)</td></tr>
<tr class="memdesc:ac7e5fc50598a5f7e9d6115b38e5c962f inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g"><td class="mdescLeft">&#160;</td><td class="mdescRight">When implemented in a derived class, paints the specified features using the specified Graphics.  <a href="#ac7e5fc50598a5f7e9d6115b38e5c962f"></a><br/></td></tr>
<tr class="memitem:a08725cc7bec0514a21819444b1d8317d inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g.html#a08725cc7bec0514a21819444b1d8317d">Show</a> (object features, Graphics g)</td></tr>
<tr class="memdesc:a08725cc7bec0514a21819444b1d8317d inherit pub_methods_class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_feature_display-g"><td class="mdescLeft">&#160;</td><td class="mdescRight">Paints the specified features using the specified Graphics.  <a href="#a08725cc7bec0514a21819444b1d8317d"></a><br/></td></tr>
</table>
<hr/><a name="details" id="details"></a><h2>Detailed Description</h2>
<div class="textblock"><p>Used to paint skeleton image. </p>
</div><hr/><h2>Member Function Documentation</h2>
<a class="anchor" id="a323c276ed8668042752709d37c4fd0e1"></a>
<div class="memitem">
<div class="memproto">
      <table class="memname">
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          <td class="memname">override void PatternRecognition.FingerprintRecognition.FeatureDisplay.SkeletonImageDisplay.Show </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_core_1_1_skeleton_image.html">SkeletonImage</a>&#160;</td>
          <td class="paramname"><em>skImg</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">Graphics&#160;</td>
          <td class="paramname"><em>g</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
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<p>Paints the specified SkeletonImage using the specified Graphics. </p>
<dl class="params"><dt>Parameters:</dt><dd>
  <table class="params">
    <tr><td class="paramname">skImg</td><td>The skeleton image to be painted. </td></tr>
    <tr><td class="paramname">g</td><td>The Graphics object used to paint the orientation image. </td></tr>
  </table>
  </dd>
</dl>

</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.Core/SkeletonImageDisplay.cs</li>
</ul>
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    <li class="navelem"><a class="el" href="namespace_pattern_recognition.html">PatternRecognition</a></li><li class="navelem"><a class="el" href="namespace_pattern_recognition_1_1_fingerprint_recognition.html">FingerprintRecognition</a></li><li class="navelem"><a class="el" href="namespace_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_display.html">FeatureDisplay</a></li><li class="navelem"><a class="el" href="class_pattern_recognition_1_1_fingerprint_recognition_1_1_feature_display_1_1_skeleton_image_display.html">SkeletonImageDisplay</a></li>
    <li class="footer">Generated on Mon May 21 2012 20:06:34 for FingerprintRecognition by
    <a href="http://www.doxygen.org/index.html">
    <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.1 </li>
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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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