Neural Networks Project: Minutiae Classification

This page describes a collection of possible projects that qualify for the examination of the elective course Neural Networks. All projects deal with aspects of fingerprint verification.

Fingerprints and Minutiae

As fingerprints differ from person to person, they can be used for purposes of verification. Fingerprints are composed of line patterns called ridges and valleys. The picture at the right shows a small part of a fingerprint. In the picture, ridges are black (dark gray) and valleys are white (light gray). Note that pores appear as white dots on the ridges. Ridges and valleys run in parallel in most places. Sometimes a ridge ends or bifurcates (a valley bifurcates where a ridge ends and vice versa). These irregularities in the pattern are called minutiae. The locations of the minutiae are very valuable in fingerprint verification: they are the features that make it possible to distinguish one fingerprint from another. The picture below shows some minutiae in a fingerprint: bifurcations are enclosed in red squares and ridge endings in yellow ones.

Goal of This Project

The central question of this project is whether minutiae can be detected by simply inspecting small segments of a fingerprint image. The segments considered are squares of 20 by 20 pixels (an entire fingerprint image is about 300 by 300 pixels). These segments should be taken as inputs of a system to be built by you. The system's output should indicate whether or not the input segment contains a minutia. A more refined output will also tell whether a detected minutia is an ending or bifurcation.

As the projects proposed here are new and have not been carried out in the past, you should not worry too much about a successful termination. You can already obtain a good mark if you can convincingly report that you have spent 50 hours of practical work and followed a promising approach (you may conclude that it turned out not to be promising at the end).

The system to be constructed should make use of techniques that have been covered in the course. Here are some suggestions:

The Databases

Test data with segments of different types can be downloaded through this page. The segments have been classified by visual inspection.

There are actually two sets of test data. The first set has been obtained from artificial fingerprints generated by the demo software available from the company OPTEL. These artificial fingerprints are binary valued (only black and white pixels). Segments extracted from them should be easier to classify.

The table below shows (magnified) example images of the three types of segments.

Ending Bifurcation Parallel lines

A data base of preclassified artificial fingerprint segments is available for downloading. Apart from the three classes mentioned, it contains a fourth class, the class of segments that contain multiple minutiae. The use of this class is optional. Note: Each segment is provided as a separate tiff file; the files have been packed by tar and gzip and can be both unpacked in a Unix/Linux environment as well as a Microsoft environment (use e.g. WinZip).

If you consider the artificial images too easy, a data base of preclassified natural fingerprint segments is available as well.

Please contact me if you think that you need a larger data base. I will try to construct a larger one.

General Remarks

Last update on: Sat Feb 26 18:07:14 MET 2000 by Sabih Gerez.