University of Twente Student Theses


Fingerprint acquisition with a smartphone camera

Oude Elferink, Wout (2014) Fingerprint acquisition with a smartphone camera.

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Abstract:Fingerprint identification systems have been used for over a century to identify individual persons. In all those years the methods for identification gradually improved. Nowadays several different systems for acquiring digital fingerprint images have been developed. Alongside the development for sensor systems, better algorithms for enhancing and comparing fingerprints have been made. Recently, the rapid developments in mobile phone technology made it possible for a big public to own a smartphone with a digital camera. Research on the use of this camera as fingerprint image capture device showed the possibilities of using it as a biometric identification system. The research done however focused on making novel algorithms starting from scratch. In this research the possibilities of using software, which is developed for dedicated fingerprint capture devices, on the images captured with a smartphone camera are explored. By using this software instead of developing an all new algorithm, the knowledge gathered over more than a decade in enhancing dedicated sensor fingerprint images can be put to use directly. In this report a new algorithm to improve smartphone captured fingerprint images is suggested. The algorithm focusses on enhancing the images in such a way that they show the same characteristics as the images from dedicated sensors. To do this, the software first segments the finger from the background, converts the image to gray scale by averaging the green and blue channel, normalizes the image according to its mean in a block size of 30x30 pixels and enhances the image according to its ridge orientation. It is shown that the enhancement algorithm improves the quality of the images drastically. A comparison test between a dedicated sensor and the smartphone camera is carried out which shows that the smartphone has a comparable performance to the dedicated sensor. Furthermore a cross operability test is done between the images from a dedicated sensor and the smartphone. While the performance does go down, it is shown that there are certainly possibilities for cross matching these fingerprints.
Item Type:Essay (Bachelor)
Faculty:TNW: Science and Technology
Subject:54 computer science
Programme:Advanced Technology BSc (50002)
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