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Intelligent Fighting Units
Kužela, Martin ; Janeček, Petr (referee) ; Drahanský, Martin (advisor)
The field training of army units includes high financial, material and human resource investments. From this reason, an emphasis on the simulator training of these units arised recently. But the training in simulator needs to have the simulated units as intelligent as a human beings are, so the field training with real human opponents can be successfully replaced with the simulator training. This work deals with the design of fighting unit's intelligent behaviour, that will be applicable in the E-COM simulator environment. Work covers the description of intelligent agents and ways how to achieve their rational and autonomous behaviour. The proposal and the analysis of intelligent fighting unit's implementation and unit's communication with surrounding environment, basic implementation of this proposal and experiments with created implementation are also described in this work.
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Firearm Type Identification in an Image
Čech, Ondřej ; Drahanský, Martin (referee) ; Dvořák, Michal (advisor)
Main goal of this work is to design, implement and test an approach for classifying firearms in an image into categories with short and long fireams, and then with single shot, multi-barreled, repeating and semi-automatic/automatic firearms. This problem was solved using SVM classifier together with Harris corner detector, FREAK descriptor and Bag of Words method. Accuracy of final program is up to 13,3 %.
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Mapping of Road Signs Using Image Processing Methods
Leško, Vladimír ; Drahanský, Martin (referee) ; Novotný, Tomáš (advisor)
The following Bachelor's Thesis deals with traffic sign recognition in video clips, obtaining GPS records and inserting traffic sings with accurate GPS co-ordinates into OSM central database. In each of Thesis' chapters are in sequence introduced methods of image detection and classification, consecutive familiarization with OSM project and its JOSM plug-in. Afterwards there will be presented an application and an applicative plug-in design and implementation process. The final chapter is represented as the results of testing the application in 10 video clips. The conclusion contains an evaluation of the Thesis with possible extensions.
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Biometric Image Data Classifier
Tretter, Zdeněk ; Drahanský, Martin (referee) ; Doležel, Michal (advisor)
The aim of this thesis is to design and implement fingerprint classifier, which classifies the fingerprints based on the scanner used. Reader is presented with existing types of fingerprint scanners and phases of classification. Designed classifier is using a cascade of classifiers, trained using the AdaBoost learning algorithm. The application was implemented in the C++ language using OpenCV library for operational systems GNU/Linux and MS Windows.
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Generation of Cryptographic Key from Eye Biometric Features
Semerád, Lukáš ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The main topic of the thesis is creation of formulas for the amount of information entropy in biometric characteristics of iris and retina. This field of science in biometrics named above is unstudied yet, so the thesis tries to initiate research in this direction. The thesis also discusses the historical context of security and identification fields according to biometric characteristics of a human being with an overlap for potential usage in biometrics of iris and retina. The Daugman’s algorithm for converting iris image into the binary code which can be used as a cryptographic key is discussed in detail. An application implementing this conversion is also a part of the thesis.
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Biometric Recognition of 3D Faces
Mráček, Štěpán ; Drahanský, Martin (referee) ; Dvořák, Radim (advisor)
Diplomová práce byla vypracována na studijním pobytu na "Gjovik University College" v Norsku, a je zpracována v angličtině. Tato práce se zabývá rozpoznáváním 3D obličejů. Je zde popsán obecný biometrický systém a také konkrétní postupy používané při rozpoznávání 2D i 3D obličejů. Následně je navžena metoda pro rozpoznávání 3D obličejů. Algoritmus je vyvíjen a testován pomocí databáze Face Recognition Grand Challenge (FRGC). Během předzpracování jsou nalezeny význačné body v obličeji a následně je trojrozměrný model zarovnán do referenční polohy. Dále jsou vstupní data porovnávána s biometrickými šablonami uloženými v databázi, a to je zajištěno využitím tří základních technik pro rozpoznávání obličejů -- metoda eigenface (PCA), rozpoznávání založené na histogramu obličeje a rozpoznávání založené na anatomických rysech. Nakonec jsou jednotlivé metody spojeny do jednoho systému, jehož celková výsledná výkonnost převyšuje výkonnost jednotlivých použitých technik.
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Perimeter Monitoring and Intrusion Detection Based on Camera Surveillance
Goldmann, Tomáš ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This bachelor thesis contains a description of the basic system for perimeter monitoring. The main part of the thesis introduces the methods of computer vision suitable for detection and classification of objects. Furthermore, I devised an algorithm based on background subtraction which uses a Histogram of Oriented Gradients for description of objects and an SVM classifier for their classification. The final part of the thesis consists of a comparison of the descriptor based on the Histogram of Oriented Gradients and the SIFT descriptor and an evaluation of precision of the detection algorithm.
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Storage Mediums within the Times
Berecz, Tomáš ; Drahanský, Martin (referee) ; Křena, Bohuslav (advisor)
This paper discusses portable storage mediums. In the begining a set of characteristics is presented, by which the storage mediums are rated, along with a division of basic types of stored information. After the definition of the characteristics a chronological overview of the storage mediums is disclosed, with a detailed description. To sum up the paper, a group of tables may be found in the end, in which the mediums are sorted acording to different characteristics.
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Biometry based on iris images
Tobiášová, Nela ; Drahanský, Martin (referee) ; Kolář, Radim (advisor)
The biometric techniques are well known and widespread nowadays. In this context biometry means automated person recognition using anatomic features. This work uses the iris as the anatomic feature. Iris recognition is taken as the most promising technique of all because of its non-invasiveness and low error rate. The inventor of iris recognition is John G. Daugman. His work underlies almost all current public works of this technology. This final thesis is concerned with biometry based on iris images. The principles of biometric methods based on iris images are described in the first part. The first practical part of this work is aimed at the proposal and realization of two methods which localize the iris inner boundary. The third part presents the proposal and realization of iris image processing in order to classifying persons. The last chapter is focus on evaluation of experimental results and there are also compared our results with several well-known methods.
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