Automatic fingerprint identification system using robust distance

Abstract EN

Fingerprint recognition has attracted many researchers in order to conduct studies in this field.

The need for finding an AFIS (Automatic Fingerprints Identification System) has been an interesting subject by scientists, bureaus and companies, because the increasing use of AFIS leads to solve many problems of identification, because there are no tools or machines in the region except classical methods.

The fingerprint department at the Criminal Identification Bureau in Erbil uses habitually very classical methods to identify the fingerprints.

There are (8000) fingerprints in that department related to criminals.

To create an AFIS, we depended on the stages of image analysis using Visual Basic.

These stages are very essential to obtain an excellent system for fingerprints recognition.

The system begins with acquiring fingerprint images of (BMP, JPEG, GIF, DIB) types and stretching (shrinking) them to (200 × 200) pixels.

The study deals with a new procedure to segment the fingerprint image via dividing the fingerprint to 64 squares, the size of each square is equal to (20 × 20) pixels.

Then, we used a new procedure to describe each square (inside the image) after representing the fingerprint image by its grayscales.

Eight parameters were used to describe the squares : Mean, Median, Quadratic mean, Harmonic mean, Variance, Skewness, Kurtosis and Mean deviation.

A robust measure for finding the minimum distances between the squares of different fingerprints was used to the recognition process and applying professional systems to perform the interpretation step to reach the end of this process, and we achieved (84.

5 %) success.