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Connection of algorithms for removal of influence of skin diseases on the process for fingerprint recognition
Heidari, Mona ; Derawi, Mohammad (oponent) ; Gomez-Barrero, Marta (oponent) ; Drahanský, Martin (vedoucí práce)
This thesis focuses on data structures, image processing, and computer vision methods for detecting and recognizing diseases in fingerprint images. The number of developed biometric systems and even used biometric characteristics is increasing. It is widely accepted that an individual's fingerprint is unique and remains relatively unchanged throughout life. However, the structure of these ridges can be changed and damaged by skin diseases. As these systems depend heavily on the structure of an individual's fingertip ridge pattern that positively determines their identity, people suffering from skin diseases might be discriminated against as their ridge patterns may be impaired. Likely, fingerprint devices have not been designed to deal with damaged fingerprints; therefore, after scanning the fingerprint, they usually reject it. The influence of skin disease is an important but often neglected factor in biometric fingerprint systems. An individual might be prevented from using specific biometric systems when suffering from a skin disease that affects the fingertips. Collecting a database of fingerprints influenced by skin diseases is a challenging task. It is expensive and time-consuming, but it also requires the assistance of medical experts and the ability to find willing participants suffering from various skin conditions on fingertips. The raw diseased fingerprint database is first analyzed to provide a solid foundation for future research. Common signs among all fingerprint images affected by the disease are found for every particular disease, and a general description of each disease and its influences is defined. Then we automatically assign the label based on a combination of the known state of the fingerprint image. The proposed solution is integrated with different algorithms focused on image processing libraries and computer vision methods for object detection. The solution has been evaluated on damaged fingerprint datasets and highlights the state of the art implementations using proposed techniques. The state of the art technique for disease detection implementations uses texture analysis and feature detection by comparing the intensity values of pixels in a small neighborhood in an image. Due to the complexity of each disease pattern, the combination of texture analysis algorithms leads to better detection results. The combination of GLCM, LBP, orientation field, and mathematical morphology can detect damage (artifacts) in fingerprint images. Combining these features makes it possible to identify changes in the texture and shape of the fingerprint flow caused by diseases. These techniques capture different aspects of the texture and shape of the damage in fingerprint images and lead to identifying changes in the texture caused by diseases. In the stages of the detection process, mathematical morphology operations are applied to improve the structural details by removing small irregularities in the image and simplify the shape of objects, making it easier to identify and isolate them expanding the boundaries of objects in an image or filling gaps and connect broken parts of objects, leading to better object detection and recognition. At the end of the detection process, coherence is applied to show the quality evaluation of fingerprint image patches into three types healthy, damaged, and background. Overall, the proposed solution showcases the effectiveness of integrating multiple image processing and computer vision algorithms for disease detection in fingerprint images.\ The combination of these algorithms can accurately detect and localize disease patterns in damaged fingerprint datasets, thus providing a reliable solution for disease detection in forensic applications.
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Algorithmic Evaluation of the Quality of Dactyloscopic Traces
Sloup, Ondřej ; Tinka, Jan (oponent) ; Drahanský, Martin (vedoucí práce)
Dactyloscopic traces are one of the critical aspects of biometric identification. They represent an element by which people can be authenticated and authorised. Nonetheless, it is necessary to evaluate if a given fingerprint is valid by the number of features it provides and decide if it is usable or useless. This analysis of features tells us how valuable the fingerprint is. We established a process that grades fingerprints based on contextual and statistical values using various enhancements and grading algorithms. These algorithms can determine if the fingerprint is good quality and whether it can be used for future processing or should be discarded. We divided fingerprints into groups based on the quality of their minutiae points, number of ridges, contrast, sinusoidal similarity and ridge thickness. We successfully evaluated fingerprints and grouped them similarly to the grouping in the NIST SD27 dataset. The algorithm's results allowed us to draw conclusions about graded fingerprints' quality and rate their usability.
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Univerzální grafický editor obrazovek pro LCD zařízení
Šmejdíř, Radek ; Drahanský, Martin (oponent) ; Orság, Filip (vedoucí práce)
Cílem této bakalářské práce bylo vytvořit pro firmu Honeywell univerzální grafický editor obrazovek pro LCD zařízení. Tento editor je jedním modulem z celé aplikace, která slouží k automatizovanému testování termostatů a podobných zařízení. Editor umožňuje definování layoutu displeje a jednotlivých obrazovek a výstup ukládá do XML souboru. Program je určen pro platformu Microsoft Windows. Implementace byla provedena v jazyce C# s využitím prostředí .NET framework.
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Analýza scény založená na 2D obrazech
Hejtmánek, Martin ; Drahanský, Martin (oponent) ; Orság, Filip (vedoucí práce)
Tato práce se zabývá analýzou povrchu objektů v jednoduché scéně reprezentované dvourozměrným obrazem. Shrnuje běžně používané metody v tomto oboru informačních technologií a popisuje jejich výhody a nevýhody. Na základě získaných znalostí a zkušeností představuje vlastní návrh algoritmu pro analýzu povrchu objektů založený na světelné informaci. Obsahuje podrobný popis algoritmu implementovaného v rámci této práce a diskutuje výsledky provedených experimentů. Na základě zkušeností s implementovaným algoritmem navrhuje možné předpoklady pro jeho další vylepšení.
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System for Recognition of 3D Hand Geometry
Svoboda, Jan ; Mráček, Štěpán (oponent) ; Drahanský, Martin (vedoucí práce)
In the last decade, there has been an increased interest in using 3D data for biometric person recognition. Perhaps the most widely researched application is 3D face recognition, where several commercial products are currently available on the market. There have been some research works on the 3D hand recognition as well, however, no commercially viable systems are currently known. Independently, in the recent years inexpensive 3D sensors have become a commodity, potentially enabling a wide range of 3D biometric applications. The main goal of this work is to develop a functioning prototype of a touchless 3D hand recognition system based on a new cheap RealSense 3D camera developed by Intel. One of the challenges in using the RealSense camera is that due to this small form factor, it produces relatively low quality samples in comparison to the more expensive acquisition hardware used in the previous research on the 3D hand biometrics. We analyze the robustness of different 2D and 3D features and study several methods for their fusion. We evaluate the performance of the system, showing that it achieves results comparable with the state-of-the-art.
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Forenzní optický komparátor otisků prstů
Dvořák, Marek ; Klubal, Ondřej (oponent) ; Drahanský, Martin (vedoucí práce)
Tato bakalářská práce se zabývá návrhem a tvorbou aplikace, která nahrazuje funkci forenzního optického komparátoru. Jsou zde popsány základní vlastnosti otisků prstů a jejich význačné body, které slouží k rozpoznávání osob. Práce s otisky prstů je velmi náchylná na kvalitu jejich obrazu. Kvůli tomu je zde popsán a implementován Gaborův filtr. Dále jsou zde popsány základní funkce pro práci s obrazem.
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Liveness Detection on Fingers Using Vein Pattern
Dohnálek, Tomáš ; Váňa, Jan (oponent) ; Drahanský, Martin (vedoucí práce)
This work presents liveness detection extension of the Touchless Biometric Systems 3D-Enroll fingerprint sensor which is based on finger vein pattern. Hardware solution was designed and realized using infrared diodes. Designed software system operates in two different modes: liveness detection based on texture features and user verification using finger vein matching. A dataset containing more than 1,100 images of both real fingers and their falsifications was gathered. Performance of both proposed modes was evaluated using mentioned dataset and suitable materials, that can fool the liveness detection module, were highlighted.
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Aplikace pro rozpoznávání sítnice lidského oka
Drozd, Radek ; Hájek, Josef (oponent) ; Drahanský, Martin (vedoucí práce)
Rozložení cévního řečiště v sítnici lidského oka je pro každého jedince unikátní, jedná se proto o velmi důležitou biometrickou charakteristiku. Zpracování barevného snímku sítnice může figurovat jako jedna z částí zamýšleného biometrického systému. V této bakalářské práci je popsán algoritmus pro automatickou extrakci cévního řečiště, lokalizaci slepé a žluté skvrny, nalezení bodů větvení cév a jejich uložení jako biometrické šablony. Algoritmus byl implementován v programovacím jazyce C++ za použití knihovny OpenCV a testován na barevných snímcích sítnice pořízených fundus kamerou. Výsledný program běží v digitálním signálovém procesoru firmy Texas Instruments. Práce obsahuje úvod do biometrie, zpracování signálů a anatomie oka.
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