This thesis deals with door video phone on the platform Raspberry Pi. There is described the platform Raspberry Pi, Raspberry Pi Camera module, operating systems for Raspberry Pi and described installing and configuring the software. Next is described the concept and description of programs created for door video phone and design of additional modules.

This diploma thesis deals with a practical application employing an industrial robot KUKA, a vision system – smart camera Siemens. The application is focused on synchronizing or robot movements with objects moving on a conveyor belt. The introductory and theoretical part of this thesis is concerned with various systems for machine vision currently available on the market. Practical part is then focused on the demonstration application: setting-up the robotic cell and description of all devices, robot and vision system programming.

Diploma thesis Monitoring of hazardous environment deals with possibilities of construction of monitoring device for the nuclear power station Temelín. In the first part are accurate requirements for monitoring device, individual risks and identify obstacles and opportunities how to overcome them. There is also description of basic options for measuring temperature and environmental monitoring. Using multi-criteria analysis was done the selection of all components, from which is possibility to construct the first development release of monitoring device. 3D models for each component and the overall design visualization facilities were created in the programming environment of Autodesk Inventor. The conclusion provides an overview of the financial cost of the equipment is assembled

This thesis covers matters related to high-speed digital cameras and their usage in various spheres of human activities, mainly in research of chip forming. Thesis summarises important knowledge needed for creation of high-speed recordings and choice of suitable lenses. Focus is taken on creation of high-speed recordings of chip forming process in turning operation outside grooving by using of different types of chipformers. Main goal is to verify its functionality in specific value range of feed per revolution.

This Master's Thesis deals with the controlling of robotic car by Raspberry Pi and the ca- mera. Theoretical part describes individual steps of image processing and probabilistic plan- ning for searching path in the work space. In particular, algorithm RRT (Rapidly-exploring Random Tree) is discussed and the balanced bidirectional RRT is further introduced and used for nonholonomic planning in configuration space. Next chapter speaks about propo- sed solution and there is the accurate description of connection Raspberry Pi to the robotic car. Rest of the work provides look at implemetation details and evaluation. In the end, conclusion was given and some improvements were suggested.

This thesis describes design and implementation of an approach to the mobile robot localization. The proposed method is based purely on images taken by a monocular camera. The described solution handles localization as an association problem and, therefore, falls in the category of topological localization methods. The method is based on a generative probabilistic model of the environment appearance. The proposed solution is capable to eliminate some of the difficulties which are common in traditional localization approaches.

Tato práce se zabývá a analyzuje možnosti, kterými je možno zjistit geografickou polohu ze snímků nebo videa pouze za použití vizuální informace z obrazu.    Výsledkem práce jsou dvě rozdílné metody geo-lokalizace. První z nich pracuje na principu hledání časů východu a západu Slunce. Hlavní výhodou této metody je její univerzálnost. Funguje s jakoukoliv kamerou umístěnou v externích prostorech a nevyžaduje přítomnost žádných specifických objektů ve scéně. Pro správný výsledek je třeba alespoň celodenní záznam z kamery. Výsledky jsou uspokojivé za každého počasí. Druhá metoda pracuje na základě analýzy stínů ve scéně. Správnou pozici je možno určit, s poměrně velkou přesností, pouze na základě dvou snímků pořízených v různém čase. Tato metoda vyžaduje přítomnost dvou objektů v obraze, které vrhají stín. Přesnosti výsledků navržených metod jsou vyhodnoceny a porovnány. Z výsledků vyplývá, že obě metody lze úspěšně použít pro odhad geografické polohy. Dále byla v rámci práce pořízena rozsáhlá datová sada obrazových sekvencí z volně přístupných webových kamer.

Motion segmentation is an important process for separating moving objects from the background. Common methods usually assume fixed camera, other approaches exist as well, but they are usually very computational intensive. This work presents an approach for scene segmentation to regions with coherent motion, which works faster than similar methods and it is capable of online processing with no prior knowledge of objects or camera. The main assumption is that the points belonging to a single objects are moving together and this applies as well in the opposite direction. The proposed method is based on tracking of feature points and searching for groups with similar motion by using RANSAC-based algorithm. Short-range repair of broken tracks is applied to increase the overall robustness of tracking. Found clusters are subsequently processed to represent separate moving objects.

This thesis deals with recognition by retina (identification, verification). In introduction we describe information about human eye, its diseases with focus on retina impact. Further (in main part) we conduct SW analyses based on biometry retina requirements and design of SW application for retina recognition. It is based on processing pipeline design (sequential application of image filters). This pipeline mostly contains filters focused on edge detection, adaptive threshold and skeletonisation. Finally, basic SW functions includes users registration (enroll), identification, verification. In conclusion we discuss experimental results and success of designed SW in practical application.

This thesis deals with complete design and manufacturing of autonomous two wheeled self-balancing robot. The goal of this thesis is to maintain the robot in up-right position and to follow black line using camera. The robot is controlled using Raspberry Pi and driven by DC motors. This thesis includes the design and implementation of hardware and software parts. Subsequently there was created the dynamic model in Matlab/Simulink. Based on this model, the LQR and PID controller was designed.