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Brute Force Attack on Fingerprint Access System Using Genetic Algorithms
Keszi, Marián ; Rydlo, Štěpán (referee) ; Kanich, Ondřej (advisor)
This work deals with a brute force attack on a fingerprint-based access system using genetic algorithms. It includes the design of a genetic algorithm as a mean to perform the brute force attack. In the study, a generative adversarial network was used as a generator of synthetic fingerprints trained on the SOCOFing dataset. Experiments were performed focusing on the possibility of inserting known information about a fingerprint fragment into the input vector, as well as experiments using advanced methods of the genetic algorithm to modify the input vector with the goal of overcoming the VeriFinger algorithm. The experiments led us to the conclusion that even with the help of a generative adversarial network and genetic algorithm, we were unable to surpass the VeriFinger algorithm.
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Precise Reconstruction of Damaged Parts in Fingerprint Images
Šmotláková, Lucia Mária ; Sakin, Martin (referee) ; Kanich, Ondřej (advisor)
The aim of the bachelor's thesis is to locate the damaged areas in fingerprints and then reconstruct them using cubic Bézier curves. Structure elements and morphological operations are used to localize the damage. The break points obtained by localization are used to plot the curve. The outcome is a simple user interface that allows the user to upload a fingerprint image and observe each step of the solution of the bachelor's thesis. The achieved results were then tested and analyzed. In conclusion, it is found that the use of Bézier curves for reconstruction is not suitable for all types of damage, in particular it is not suitable for large damage in areas of high curvature.
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Integration of tools working with fingerprints
Dobeš, Kristián ; Sakin, Martin (referee) ; Kanich, Ondřej (advisor)
This bachelor thesis deals with the design and implementation of the integration of tools working with fingerprints into current application SyFDaS. The main goal was to extend existing features of the application and develop new ones, such as visualization of simulated damage, damage annotation and generation of random input parameters for simulation. In the work, a methodology for integrating the new tools into the application was presented and successfully demonstrated. During the course of the work, the current user interface was greatly enhanced to better support different types of damage. The integration and extensions of tools were implemented in the C# programming language, including a reworking of the tools from Python using the EmguCV library for image processing. In the final part, quality analysis of the integrated tools with new extensions and testing of user interface friendliness were performed to confirm the functionality and usability of the application.
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Animal Identification Based on Biometric Information
Jančeková, Lucia ; Sakin, Martin (referee) ; Dyk, Tomáš (advisor)
Táto práca sa zaoberá identifikáciou divej zvery, konkrétne diviaka pomocou fotografii nosu. Ide o identifikáciu jednotlivcov a využívajú sa na to ryhy, ktoré sa nachádzajú na vrchnej časti nosu. V rámci tejto práci je navrhnuté a implementované riešenie na extrakciu tejto biometrickej informácii a porovnaním ju s ostatnými už uloženými šablónami. Riešenie je otestované na fotografiách z rovnakého diviaka, ale aj na 49 ďalších individuálnych jedincov.
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Reconstruction of Damaged Parts of Fingerprint Image Using Neural Nets
Bobocký, Boris ; Dyk, Tomáš (referee) ; Kanich, Ondřej (advisor)
In this paper, I propose a method for reconstructing damaged fingerprints using generative adversarial networks (GANs), implemented with Python and the PyThorch library. I have trained a specific GAN model on a dataset of approximately twenty thousand prints, created with Anguli and other damage simulation tools. This approach produced excellent results and could have wide application in biometric systems. This work highlights the potential of deep learning in the fields of image reconstruction and biometrics.
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Algorithmic Evaluation of the Quality of Dactyloscopic Traces
Sloup, Ondřej ; Tinka, Jan (referee) ; Drahanský, Martin (advisor)
Daktyloskopické stopy jsou jedním z klíčových aspektů biometrické identifikace. Reprezentují způsob, jakým lidé mohou ověřit svou identitu a být autorizováni. Nicméně je důležité ohodnotit, jestli daný otisk je validní a jestli dokáže poskytnout dostatek informací na to, aby bylo možné určit, jestli je použitelný anebo ne. Tato analýza rysů otisku dokáže specifikovat, jak moc přínosné pro nás je se daným otiskem zabývat. Navrhli jsme proces, který hodnotí otisky prstů na základě kontextuálních a statistických výsledků. Ne vždy je otisk ve stavu, kde všechny jeho prvky jsou viditelné a je nutné odstranit rušivé elementy před samotným ohodnocením, které by mohli negativně ovlivnit výsledky algoritmů pro hodnocení kvality. Tyto algoritmy rozpoznávají, jakou kvalitu má otisk prstu a jestli bude použit na další proces anebo zahozen. Rozdělili jsme otisky do skupin pomocí jejich kvality, která se hodnotila na základě počtu markantních bodů, počtu papilárních linií, kontrastu, sinusové podobnosti a tloušťky papilárních linií. Úspěšně jsme ohodnotili otisky a rozdělili je podobně jako v NIST SD27 databázi. Z výsledků těchto algoritmů jsme schopni ohodnotit otisky na základě jejich kvality, a tak vyvodit jejich použitelnost.
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Reconstruction of Damaged Parts of Fingerprint Image
Halva, Vladislav ; Drahanský, Martin (referee) ; Kanich, Ondřej (advisor)
This bachelor thesis deals with the reconstruction of damaged fingerprint areas. The main goal is the design and implementation of an algorithm for the reconstruction of these regions. The designed algorithm consists of three main parts. The first part is fingerprint feature extraction and their derivation in damaged areas. The second part is a localization of damaged areas, which is based mainly on the structure of papillary lines. The last part is the damaged areas reconstruction itself. Gabor filter is used in this part of the process. The algorithm is implemented in C++ using the OpenCV library. An analysis of the reconstruction success rate is done afterwards. It is at first evaluated using the difference of quality between the input and processed fingerprint image, estimated by NIST NFIQ 2.0 and one other alternative tool for fingerprint image quality evaluation. The next step is a manual evaluation of the reconstruction success rate in various types of damaged areas.
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Presentation Attack Detection on Hand Sensing Technology in Infrared Area
Richtarik, Jakub ; Sakin, Martin (referee) ; Drahanský, Martin (advisor)
When verifying a fingerprint, an attacker can use a counterfeit made of synthetic material. This can be prevented, for example, by using multispectral analysis, when various materials have different reflectance for certain wavelengths. There are several studies that have addressed this, but have always focused on one finger. The aim of this work is liveness detection on the whole palm and fingers, as on a larger object, which will contribute to even higher level of security. In the final solution, a NIR camera was used to capture the dataset, which is used to train a convolutional network to determine whether it is a living hand or a counterfeit.
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