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Image registration
Jindra, Jakub ; Jiřík, Radovan (referee) ; Krátká, Lucie (advisor)
This bachelor thesis deals with various methods of image registration in the medical treatment. The criterias are elaborated for selecting the correct method of registration. This work describes parameters for proper transformation, identification, registration proces, a final assessment of registration for its approval and the corresponding evaluation. Some basic programs have already concerned with image registration and they are accompanied by basic information. This semester thesis also describes the basics of working with MRI and the creation of anatomical atlas from the magnetic resonation rat’s brain. In conclusion is described the creation of a simple graphical interface for viewing images of brain obtained from the magnetic resonance. Furthermore, the work deals with the registration of images according freely available programs and the related system of evaluation of these results. The scoring system is processed in a graphical users interface Matlab, where is used histograms, mosaic and evaluation using the cross.
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Similarity Measure of Points of Interest in Image
Křehlík, Jan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This document deals with experimental verifying to use machine learning algorithms AdaBoost or WaldBoost to make classifier, that is able to find point in the second picture that matches original point in the first picture. This work also depicts finding points of interest in image as a first step of finding correspondence. Next there are described some descriptors of points of interest. Corresponding points could be useful for 3D modeling of shooted scene.
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Automatic Photography Categorization
Matuszek, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deal with choosing methods, design and implementation of application, which is able of automatic categorization photos based on its content into predetermined groups. Main steps of categorization are described in greater detail. Finding and description of interesting points in image is implemented using SURF, creation of visual dictionary by k-means, mapping on the words through kd-tree structure. Own evaluation is made for categorization. It is described, how the selected steps were implemented with OpenCV and Qt libraries. And the results of runs of application with different settings are shown. And efforts to improve outcome, when the application can categorize right, but success is variable.
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Automatic Photography Categorization
Veľas, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to create an application, which is would be able to achieve sufficient precision and computation speed of categorization. Basic solution involves detection of interesting points, extraction of feature vectors, creation of visual codebook by clustering, using k-means algorithm and representing visual codebook by k-dimensional tree. Photography is represented by bag of words - histogram of presence of visual words in a particular photo. Support vector machines (SVM) was used in role of classifier. Afterwards the basic solution is enhanced by dividing picture into cells, which are processed separately, computing color correlograms for advanced image description, extraction of feature vectors in opponent color space and soft assignment of visual words to extracted feature vectors. The end of this thesis concerns to experiments of of above mentioned techniques and evaluation of the results of image categorization on their usage.
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Automatic Content-Based Image Categorization
Němec, Ladislav ; Španěl, Michal (referee) ; Veľas, Martin (advisor)
This thesis deals with automatic content-based image classification. The main goal of this work is implementation of application which is able to perform this task automatically. The solution consists of variable system using local image features extraction and visual vocabulary built by k-means method. Bag Of Words representation is used as a global feature describing each image. Support Vector Machines - the final component of this system - perform the classification based on this representation. In the last chapter, the results of this experimental system are presented.
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Optic flow software module design
Grulich, Jan ; Růžička, Michal (referee) ; Věchet, Stanislav (advisor)
This bachelor thesis is focused on the analysis of optical flow. The first part is dedicated to the theoretical analysis of the motion of image features. Especially important is finding quality features that can be tracked in a videosequence. Detailed mathematical description of the necessary algorithms is presented. The second part describes the software and its functions with the implemented algorithms. The main function is determining the distance of an object from the camera based on its velocity. Empirical tests of this function are presented.
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Detection of Corresponding Points in Images
Komosný, Petr ; Hradiš, Michal (referee) ; Španěl, Michal (advisor)
This thesis is interested in detection of corresponding points in images, which display the same object, eventually some of important elements and synchronizing these images. The aim of this thesis is to find, study and choose suitable algorithm for detecting interesting points in image. This algorithm will be apply at couple of images and in these images will find couples of corresponding points across these images. Functional output of this thesis will be application which will realize choosen interesting points detector, algorithm for finding correspondencies of regions and their synchronizing and joint them to one output image.
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Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
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Interest-Point Detection on CUDA
Ryba, Jan ; Řezníček, Ivo (referee) ; Herout, Adam (advisor)
Corner point detection is one of many functions used in computer vision for tasks such as tracking, detecting objects, comparing images and much more. Many of the algorithms are complex and require a lot of CPU time. This is where the CUDA platform comes in. CUDA kernels run parallely on graphic accelerators can rapidly decrease time needed for execution, allowing even these complex calculations to work in real time or even better. Text focuces on Moravec and Harris corner detection algorithms and their effective implementation on CUDA. Examination of potetntial and performance of CUDA platform is also importatnt.
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Eye Tracking in User Interfaces
Jurzykowski, Michal ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
Tato diplomová práce byla vytvořena během studijního pobytu na Uviversity of Estern Finland, Joensuu, Finsko. Tato diplomová práce se zabývá využitím technologie sledování pohledu neboli také sledování pohybu očí (Eye-Tracking) pro interakci člověk-počítač (Human-Computer Interaction (HCI)). Navržený a realizovaný systém mapuje pozici bodu pohledu/zájmu (the point of gaze), která odpovídá souřadnicím v souřadnicovém systému kamery scény do souřadnicového systému displeje. Zároveň tento systém kompenzuje pohyby uživatele a tím odstraňuje jeden z hlavních problémů využití sledování pohledu v HCI. Toho je dosaženo díky stanovení transformace mezi projektivním prostorem scény a projektivním prostorem displeje. Za použití význačných bodů (interesting points), které jsou nalezeny a popsány pomocí metody SURF, vyhledání a spárování korespondujících bodů a vypočítání homografie. Systém byl testován s využitím testovacích bodů, které byly rozložené po celé ploše displeje.
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