A framework in C# for fingerprint verification (Source : Code Project)

August 4, 2010 § 6 Comments

A framework in C# for fingerprint verification


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.

Download FingerprintRecognition.zip – 225.88 KB

Download Help.zip – 1.5 MB

Introduction

Fingerprint recognition [1] is an active research area nowadays. An
important component in fingerprint recognition systems is the
fingerprint matching algorithm. According to the problem domain,
fingerprint matching algorithms are classified in two categories:
fingerprint verification algorithms and fingerprint identification
algorithms. The aim of fingerprint verification algorithms is to
determine whether two fingerprints come from the same finger or not. On
the other hand, the fingerprint identification algorithms search a query
fingerprint in a database looking for the fingerprints coming from the
same finger.

There are hundreds of papers concerning to fingerprint verification
but, as far as we know, there is not any framework for fingerprint
verification available on the web. So, you must implement your own tools
in order to test the performance of your fingerprint verification
algorithms. Moreover, you must spend a lot of time implementing
algorithms of other authors to compare with your algorithms. This was
our motivation to put our fingerprint verification framework available
for everyone.

The most closely related work to our framework is the FVC-onGoing web system. This system has the following limitations:

  • You do not have access to any algorithm but yours.
  • It is not a framework; so, you cannot reuse any software component.
  • It cannot be used with educational purpose because students cannot see how the algorithms work.
  • After performing an experiment using a database (standard or hard)
    you must wait 30 days to perform another experiment using the same
    database.
  • You do not have control over the fingerprint databases. Thus, you
    cannot use your own databases neither modify the existing ones.
  • You do not have access to the fingerprints that your algorithm fails
    matching. Hence, you cannot analyze why the algorithm fails in order to
    fix your code.
  • You cannot create an experiment with a custom protocol for performance evaluation.

 

If any of the above mentioned limitations constitute a problem for you, then you should use our framework.

Our framework is implemented in C# with .Net Framework for two main
reasons. First, C# has become one of the most popular programming
languages. Second, the technologies, tools and class libraries available
on .Net Framework save us a lot of time of coding.

Our framework allows performing fingerprint verification experiments
for databases B of FVC2000, FVC2002 and FVC2004; and databases A of
FVC2004. In this experiments, we use the performance indicators of the
Fingerprint Verification Competitions [2] (EER(%), FMR100(%),
FMR1000(%), ZeroFMR(%), Time(ms) and ROC curves). Additionally, you can
include experiments with a custom evaluation protocol or different
databases.

We implemented the fingerprint verification algorithms proposed by
Tico and Kuosmanen [3], Jiang and Yau [4], Medina-Pérez et al. [5] and
Qi et al. [6]. It is important to highlight that, despite the algorithm
of Qi et al. is a combination of a minutiae matching algorithm with an
orientation based algorithm, we implemented only the minutiae matching
algorithm. This framework allows you to include new fingerprint matching
algorithms as well as new feature extraction algorithms with minimum
effort and without recompiling the framework.

One of the goals that we kept in mind while developing this framework
was to achieve class interfaces as simple as possible. This way, adding
new algorithms is pretty straightforward.

We hope this work motivates you and more people to collaborate with us in order to implement more algorithms.

In this article we briefly explain how:

  • to perform fingerprint verification experiments,
  • to see the matching minutiae after performing an experiment with a minutiae based algorithm,
  • to compute and display features from certain fingerprint,
  • to integrate your algorithms to the framework.

 

Before using the framework

With this article, we provide the following files:

 

Before doing anything else, download the binary files containing the features of the fingerprints at http://rapidshare.com/files/409648016/FingerprintFeatures.rar. Then, extract the file FingerprintFeatures.rar and populate the directories with the image of fingerprints available at:

 

Running a fingerprint verification experiment

Extract the file “FingerprintRecognition.zip” and build the solution.
Then you can debug the project “FR.FVCExperimenter” or you can execute
“FR.FVCExperimenter.exe” in the directory containing the generated
assemblies. The following window will open:

In the “Resources” text box, specify the path of the database that
you are going to use, for example: “D:\PR
Databases\Fingerprints\FVC2004\DB1_B”.

Select the proper experiment type in the combo box with label
“Experiment”. Select value “FVCDB_B” if you are going to perform an
experiment with any of the databases DB1_B, DB2_B, DB3_B or DB4_B.
Select value “FVC2004DB_A” if you are going to perform an experiment
with any of the databases DB1_A, DB2_A, DB3_A or DB4_A of FVC2004.

Use the combo boxes “Minutia Extractor”, “Orientation Image
Extractor” and “Skeleton Image Extractor“ to select the algorithms that
will be used to compute the basic features (minutiae, orientation image
and skeleton image). Sadly, we are not specialists in digital image
processing. That is why we only implemented the algorithm proposed by
Ratha et al. [7] to extract orientation images. The minutiae and
skeleton images were computed by a collaborator which gave us these
features saved in binary files. We hope this work motivates you and more
people to collaborate with us in order to implement other feature
extraction algorithms as well as matching algorithms.

Use the combo box with label “Matcher” to select a fingerprint
verification algorithm, and the combo box with label “Feature Provider”
to select the algorithm that will be used to store and retrieve the
features for the selected matcher. Despite that we implemented only one
feature provider for each matcher, there are possible scenarios where
you may have multiple feature providers for each matcher.

The grid with label “Properties” allows changing the parameters of any selected algorithm.

Click on “Execute Experiment” button to run the experiment. This
experiment uses the evaluation protocol of the Fingerprint Verification
Competitions [2]. The performance indicators computed in this
experiments are: EER(%), FMR100(%), FMR1000(%), ZeroFMR(%), Time(ms) and
ROC curves. These indicators are saved in a file which name is formed
by the name of the matching algorithm concatenated with “.Summary.csv”.
This file is saved in a folder by the name of “Results” in the same
folder where the fingerprints are stored. Two more files are saved, one
file containing the false matching fingerprints and the other containing
the false non matching fingerprints.

If you want to match two fingerprints and verify the coincident
minutiae, then click the “Visual Match” button which will open the
“Visual Fingerprint Matching” form. Load the fingerprints that you want
to compare and click the “Match” button. The feature extractors and
matcher selected in the “FVC Experimenter” are also used here to perform
the fingerprint matching. The following is an example of matching two
fingerprints:

Visualizing features

If you want to visualize features for certain fingerprint then you
can use “FR.FeatureDisplay” project. In “Fingerprint Feature Display”
form, you can change the feature extractor and feature display. In the
framework, we include classes to visualize minutiae, orientation image
and skeleton image.

The following is an example visualizing the orientation image of a fingerprint:

Adding new algorithms to the framework

The first thing that you need to know is that you do not need to
modify the applications of the framework in order to recognize your
algorithms because we use Reflection to load all algorithms dynamically
at execution time.

You may create as many assemblies as you want in the directory
containing the framework. For each new assembly go to the properties and
set the output path with value “..\bin\Release\”.

In order to add a new feature extractor, you must inherit from the generic class FeatureExtractor<T> and implement the method ExtractFeatures(Bitmap image). For example, suppose that you want to create an extractor for features of type MyFeature, then you could implement a class like the following:

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public class MyFeatureExtractor : FeatureExtractor<MyFeature>{	public override MyFeature ExtractFeatures(Bitmap image)	{		// Place here your code to extract features	}       }

In case that your new features are built upon some existing features then you can do like follows:

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public class MyFeatureExtractor : FeatureExtractor<MyFeature>{         public FeatureExtractor<List<Minutia>> MtiaExtractor { set; get; }

    public FeatureExtractor<OrientationImage> OrImgExtractor { set; get; }

    public override MyFeature ExtractFeatures(Bitmap image)    {	try        {             var mtiae = MtiaExtractor.ExtractFeatures(image);             var orImg = OrImgExtractor.ExtractFeatures(image);             return ExtractFeatures(mtiae, orImg);        }        catch (Exception)        {             if (MtiaExtractor == null)                throw new InvalidOperationException("Cannot extract MyFeature: Unassigned minutia list extractor!");             if (OrImgExtractor == null)                throw new InvalidOperationException("Cannot extract MyFeature: Unassigned orientation image extractor!");             throw;        }    }

    public MyFeature ExtractFeatures(List<Minutia> mtiae, OrientationImage orImg)    {        // Place here your code to extract features    }       }

For each feature extractor you must create a resource provider.
Resource providers allow saving (retrieving) to (from) file the
resources associated to fingerprints. The framework includes resource
providers for extractors of minutiae (MinutiaListProvider), orientation image (OrientationImageProvider) and skeleton image (SkeletonImageProvider). The following is an example of a resource provider for the feature extractor defined above.

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public class MyFeatureProvider : ResourceProvider<MyFeature>{    public MinutiaListProvider MtiaListProvider { get; set; }

    public OrientationImageProvider OrImgProvider { get; set; }

    public override string GetSignature()    {        return "myf";

    }

    public override bool IsResourcePersistent()    {        return true;    }

    protected override MyFeature Extract(string fingerprint, ResourceRepository repository)    {        try        {            var mtiae = MtiaListProvider.GetResource(fingerprint, repository);            var orImg = OrImgProvider.GetResource(fingerprint, repository);            return featureExtractor.ExtractFeatures(mtiae, orImg);        }        catch (Exception)        {            if (MtiaListProvider == null)                throw new InvalidOperationException("Unable to extract MyFeature: Unassigned minutia list provider!");            if (OrImgProvider == null)                throw new InvalidOperationException("Unable to extract MyFeature: Unassigned orientation image provider!");            throw;        }    }

    private MyFeatureExtractor featureExtractor = new MyFeatureExtractor();}

Now, it is time to create a new fingerprint matching algorithm. Suppose that you want to match features of type MyFeature, then you must create a matcher like this:

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public class MyMatcher : Matcher<MyFeature>{            public override double Match(MyFeature query, MyFeature template)    {        // Place here your code to match fingerprints    }}

In case that you are implementing a minutia matching algorithm then you should modify the above code as follows:

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public class MyMatcher : Matcher<MyFeature>, IMinutiaMatcher{            public override double Match(MyFeature query, MyFeature template)    {        List<MinutiaPair> matchingMtiae;        return Match(query, template, out matchingMtiae);    }

    public double Match(object query, object template, out List<MinutiaPair> matchingMtiae)    {        // Place here your code to match fingerprints    }}

Conclusions

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. We
provide several matching algorithms that you can use not only for
experimental purpose, but also to create your own applications. We
provide the source code of all the algorithms so the user can reuse any
part of the code as well as any software component.


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