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Microsystems, Electronics and Acoustics
ISSN 2523-4447 · e‑ISSN 2523-4455 Open Access · CC BY-SA 4.0
Vol. 26 · Issue 2 · 2021 Aug 31, 2021 Electronic Systems and Signals

Dactylogram Processing System

ВЖ
Вадим Денисович Желудков Corresponding Національний технічний університет України "Київський політехнічний інститут імені Ігоря Сікорського",National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine
ТТ
Тетяна Олександрівна Терещенко Національний технічний університет України "Київський політехнічний інститут імені Ігоря Сікорського",National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine
ЮЯ
Юлія Сергіївна Ямненко Національний технічний університет України "Київський політехнічний інститут імені Ігоря Сікорського",National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” ,National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine
Pages236123-1 - 236123-7 PublishedAug 31, 2021
PDF (Ukrainian)
VOL 26 · ISS 2 · 2021 View issue

Abstract

Recognition of fingerprints (dactyloscopic images) is one of the practical application of signal processing. System of person identification by fingerprints is commonly-used by law enforcement bodies and Border services. This is also important in the field of access control systems and commercial devices where data security is not less important as reliability and data rate of processing algorithms. Existing systems of fingerprints processing are not fully ready for automatic recognition. Also, full modernization of existing equipment is not possible. The paper is devoted to the method of image processing. In particular, the preliminary processing of dactyloscopic images is considered as well as development of theoretical approach and practical realization of first stage of patterns forming – pre-processing of image for decreasing of its size and contrast increasing. The criteria for selecting ranges for sampling and quantization of images are given. Tasks of reducing the fingerprint image while increasing the contrast of the image were considered, analyzed and solved. Image reduction is based on the use of interpolation. It is shown that among the considered interpolation methods - linear, bilinear and bicubic - the latter one could provide the highest accuracy although it needs more hardware resources. However, when the dpi parameter (dots-per-inch) falls below 150, a rapid increase in the number of artifacts in the image is observed. Increasing of image sharpness is necessary for highlighting of colour transitions and consequently – for increasing the percentage of correct recognitions. Such increasing of image sharpness is proposed to achieve by using the Laplace operator (Laplasian calculation) and adding the result to the original image. The value of derivative at each pixel of the image depends linearly on sharpness level. Thus, it allows separating the areas with abrupt colour changes and gaps from the areas where the brightness is constant or changes slowly. The result of second derivative is much more for the areas with sharp changes than for the areas without them. The areas with constant or slowly-changing brightness after the second derivative calculation become almost the same dark colour. These areas could be restored to original image with retention of sharpness increasing effect. For this, transformed by Laplasian image should be added to the original one. Use of Laplasian allows to get an acceptable balance between the speed and computational complexity of the fingerprint recognition algorithm. The technical implementation of the device and illustration of its operation are given. Fingerprints image processing system is executed on the base of STM32f407 microcontroller with CortexM core. The system includes capasitive scanner, TFT LCD display and lab power source. The microcontroller software realizes, in particular, interpolation and contrast increasing. The system is module-compatible and able for scaling.

Keywords

#fingerprint image #interpolation #Laplace operator

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