The aim of this master's thesis was to design, develop and test a method for lossless image compression. The theoretical part includes a description of selected exiting methods such as RLE, MTF, adaptive arithmetic coding, color models used in LOCO-I and JPEG 2000, predictors MED, GAP and laplacian pyramid. The conclusion includes a comparison of various combinations of chosen approaches and overall efficiency compared with PNG and JPEG-LS.

Ultrasound imaging is widely used in medical examination. However, the interpretation of images is not trivial and requires much experience. In this thesis, various techniques for enhancement of visual quality of ultrasound images are presented. Several basic and advanced methods that may simplify the visual diagnosis are described. Finally, an interactive application is designed and implemented for simple usage of presented methods.

The project is focused on methods of obtaining large number of images of human faces. Such database should then serve as a set of data for face detection and recognition by the means of supervised machine learning. The work deals with the basic principles of supervised machine learning and available data sets for this procedure. Project contains proposals of techniques and implementation of algorithms suitable for acquiring images from video and a concept of user interface for semi-automatic acceptation and annotation of located images.

The goal of this thesis is to describe barcodes used in real world applications and to create application for real time detecting and decoding of chosen barcodes using computer vision. Normal linear barcode is first introduced, and then two dimensional matrix barcode is described with focus on its origin, usage and structure. Especially the process of localization, encoding and decoding of QR Code, which is chosen for future use in work, is described mainly. Also briefly description of computer vision and OpenCV library is available. Next the concept and implementation of application for localization and recognition of QR Codes is described. Finally description of testing, evaluation of thesis and ways of improvements are discussed.

This thesis concerns the background reconstruction from several photographs (so called depopulation scene efect). There are presented methods for obtaining the background from video and discussion of their use for photographs. The greatest emphasis is placed on the Gaussian mixture model and effort to improve this algorithm due to static image. The photographs should be taken with a tripod.

Existing systems of scene reconstruction and theorethical basics necessary for scene reconstruction from images data are described in this work. System of scene reconstruction from video was designed and implemented. Its results were analyzed and possible future work was proposed. OpenCV, ArtToolKit and SIFT libraries which were used in this project are also described.

This paper deals about AdaBoost algorithm, which is used to create a strong classification function using a number of weak classifiers. We familiarize ourselves with modifications of AdaBoost, namely Real AdaBoost, WaldBoost, FloatBoost and TCAcu. These modifications improve some of the properties of algorithm AdaBoost. We discuss some properties of feature and weak classifiers. We show a class of tasks for which AdaBoost algorithm is applicable. We indicate implementation of the library containing that method and we present some tests performed on the implemented library.

The focus of this thesis is the cooperation of cameras and projectors in projection of data into a scene. It describes the means and theory necessary to achieve such cooperation, and suggests tasks for demonstration. A part of this project is also a program capable of using a camera and a projector to obtain necessary parameters of these devices. The program can demonstrate the quality of this calibration by projecting a pattern onto an object according to its current pose, as well as reconstruct the shape of an object with structured light. The thesis also describes some challenges and observations from development and testing of the program.

This master thesis is engaged in development of software tool intended for measuring of status of lower limb bones. It analyzes status of the feet and lower limb and defines significantpointsonthem.Alsoanalyzesdesignoptionsofmeasuringsceneandmarkers and describe the one selected. In another part is described automated point recognition algorithm. The last part describes graphical user interface, where are these algorithms implemented.

This thesis deals with recognition of vehicles with image captured by one camera. The image is always taken as a front view of a vehicle passing one specific place in case of various lighting conditions. The aim is to implement classification method with regard to robustness, reliability and computional complexity. The method is implemented in Mircosoft Visual Studio 2013 using the OpenCV library.