|
|
New technologies for biometric recognition based on hand characteristics
Dvořák, Michal ; Jadlovský, Ján (oponent) ; Marcialis, Gian Luca (oponent) ; Drahanský, Martin (vedoucí práce)
Biometrics allows us to identify or verify people based on their physical characteristics. Although the recognition itself may be very fast, extracting the chosen biometry features in the real world is a non-trivial task. To perform a recognition on a large number of people, for example at an airport, we need to perform the scanning and recognition in the shortest possible time, ideally without the user having to stand still. In this dissertation thesis, I focus on the development of a touchless and therefore hygienic biometric system, capable of performing identification, feature extraction and subsequent recognition on the fly using hand characteristics, and other systems and algorithms needed to solve this complex problem. This thesis presents the current state of research and development in the field of biometric identification based on selected hand characteristics, with a focus on identification using hand geometry and fingerprints. Further it also discusses the technological principles used for the collection of the characteristics. According to the dissertation objectives, formulated on the basis of the research, the practical part of this thesis deals with the development of biometric systems for use to identify large numbers of people in flight, for which most current biometric systems based on hand characteristics are not suitable. The thesis then addresses related issues, in particular presentation attack detection and biometric multimodality.
|
|
|
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.
|
|
|
Automatická evaluace multi-biometrických systémů
Štupák, Richard ; Hrubý, Martin (oponent) ; Mráček, Štěpán (vedoucí práce)
Tato bakalářská práce se věnuje problematice evaluace multi-biometrických systémů a způsobům fúze biometrických vlastností. První část vysvětluje pojmy z biometrie, biometrických a multi-biometrických systémů. V další části je popis návrhu a implementace jednotlivých částí aplikace. Poslední část obsahuje experimenty s vytvořenou aplikací nad testovacími daty. Cílem testování bylo ověření, zda aplikace dokáže najít způsob fůze pro dosáhnutí lepších výsledků.
|
|
| |
|
|
Přístupový systém se snímači otisků prstů
Tříska, Martin ; Kučera, Pavel (oponent) ; Macho, Tomáš (vedoucí práce)
Tato práce popisuje kompletní návrh přístupového systému s využitím biometrických dat, aplikovatelného v menších firemních objektech. V první části je krom úvodu do problematiky snímání otisků prstů popsán také výběr komunikačního rozhraní mezi terminály a nadřazeným systémem. Druhá část práce se již zabývá praktickou realizací systému a to jak z pohledu hardware, tak i software.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
| |
|
|
Senzory snímání otisků prstů
Slezák, Jakub ; Frýza, Tomáš (oponent) ; Fedra, Petr (vedoucí práce)
Bakalářská práce je zaměřena na možnosti bezprostředního snímání daktyloskopických otisků a jejich využití pro identifikaci osob. Náplní práce je zhodnotit technologie kontaktního a bezkontaktního snímání otisků prstů. V práci je popsán návrh a realizace optického snímače otisku prstů s příslušným softwarem a jsou zhodnoceny dosažené výsledky.
|
host ::
RSS.