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Finger vein biometrics
Bělehrádek, Stanislav ; Sekora, Jiří (referee) ; Mézl, Martin (advisor)
This thesis presents basic concepts in the field of biometrics, with a focus on optical methods of finger vein biometrics. The paper also contains additional information including physics and anatomy terms, which are important for understanding presented problems. Part of the thesis is draft of the device used for finger vein biometry and proposal of effective image preprocessing process for biometric purpose. Main part of the thesis contains creation and testing of such device. User interface is created in MATLAB and allows identification and verification of people with record in database. Biometric system is tested on group of 16 individuals. Achieved results are discussed and compared with results of similar devices.
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Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
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Multimodal Registration of Fundus Camera and OCT Retinal Images
Běťák, Ondřej ; Čmiel, Vratislav (referee) ; Gazárek, Jiří (advisor)
Tato práce se zabývá multimodální registrací snímků sítnice z různých skenovacích zařízení. Multimodální registrace umožňuje zvýraznit prvky na snímcích sítnice, které jsou důležité pro detekci různých typů onemocnění oka (jako je glaukom, degradace nervových vláken, degradace cév, atd.). Teoretická část tvoří zhruba první půlku práce a je následována praktickou částí, která popisuje postupy při různých typech registrací snímků z fundus kamery, SLO a OCT. Registrace fundus a SLO snímků je provedena pomocí prostorové transformace. Tato práce popisuje tři různé metody registrace SLO snímků se snímky z fundus kamery. První a zároveň nejjednodušší je manuální registrace. Druhou je automatická registrace založená na metodě korelace. Výsledky, včetně porovnání obou metod, jsou uvedeny v závěru. Třetím typem je poloautomatická registrace, která využívá výhod obou předchozích metod a tím pádem je kompromisem mezi rychlostí a přesností registrace. Registrace fundus snímků a B-scanů z OCT je realizována dvěma různými metodami. První je opět založená na korelaci a druhá na prostorové transformaci. Všechny tyto registrační metody jsou realizovány také prakticky v programovém prostředí Matlab.
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Raster to Vector Conversion
Siblík, Jan ; Venera, Jiří (referee) ; Šilhavá, Jana (advisor)
This bachelors thesis inspects an issue of converting a raster image into vector representation. It describes theoretical basis for image preprocessing techniques, theory and means of edge detection and some possible techniques of image vectorization. It also desribes designing and realization of a demostrative aplicetion, which is the programming part of this thesis.
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Supporting processing of tomographic data for 3D Slicer
Dašek, Filip ; Harabiš, Vratislav (referee) ; Čmiel, Vratislav (advisor)
Thesis summarize available softwares for visualization and segmentation of medical data. Main focus is on open source software 3D Slicer, where all main modules and functions for processing and segmentation of 3D images are described. The reader is also acquaint with posibility to create new modules and function in Python. In practical part of thesis new modul is created. Modul is focused on fast and effective segmentation of heart and their parts by using watershed method. Part of the module are tools for preprocessing of CT images and automatic post-processing. GUI was implemented and created with QT designer. Thesis containts testing and presenting segmented data. Segmentation by presented modul generaly achieves better results then options offered by 3D Slicer. In the last part of thesis is presented proposal for usage of supporting funtions for fast and efective segmentation of heart and his parts.
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Mobile System for Text Recognition on Android
Tomešek, Jan ; Kolář, Martin (referee) ; Zemčík, Pavel (advisor)
This thesis deals with creation of a mobile library for preprocessing of images with text which represents a part of a system for text recognition. The library is realized with emphasis on generality of use, efficiency and portability. The library providing a set of algorithms primarily for image quality assessment and text detection was created in this thesis. These algorithms enable a substantial decrease in volume of transmitted data and speed up and refinement of the recognition process. An example application for the Android platform able to analyze composition of foods stated on their wrappings was created as well. Overall, the library (system) simplifies development of mobile applications with focus on text extraction and analysis. The mobile application then provides a comfortable way of food harmfulness verification. The thesis offers a reader an overview of current solutions and tools available in this field, it provides a breakdown of important image preprocessing algorithms and guides him through the construction of the library and the application for mobile devices.
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Digital image analysis of mitotic chromosomes
Jaroš, Luboš ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
The development in modern medicine has allowed to study human genome and detect predispositions to several diseases. One of very promising techniques is the analysis of human karyotype, i.e., the number and appearance of chromosomes in the cell nucleus. The most important step in the karyotype analysis is the chromosome detection and categorization. In this work, a new algorithm for detection of chromosomes from an image of microscopic DNA sample and their categorization into seven groups was developed. The algorithm was implemented in Matlab. The accuracy of segmentation and classification was tested on a set of images from two databases with 117 and 38 images, respectively. The sensitivity of the developed segmentation reached 88% while the value of positive predictivity of segmentation reached 92%. The success rate of chromosome pairing achieves 77%.
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