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This diploma thesis deals with the issue of the recognition of road signs in the video sequence. Such systems increase the traffic safety and are implemented by major car factories in the manufactured cars (Opel, BMW). First, the motivation for the utilisation of these systems is presented, followed by the survey of the current state of the art methods. Finally, a specific road-sign detection method is chosen and described in detail. The method uses advanced techniques of signal processing. Segmentation method in color space is used for sign detection and subsequent classification is accomplished by linear classification with optional use of PCA method. In addition, the method contains the prediction of road sign positions based on Kalman filtering. Implemented system yields relatively accurate results and overall analysis and discussion is enclosed.

This thesis deals with the processing of stereo images. It described the principles of calibration and rectification of stereo images. The thesis described several methods for finding important points. SURF method is then implemented for practical solution. Finding correspondences is realized using the methods of image processing library OpenCV. Reconstructed spatial coordinates of points and write by the format specified VRML97. Finally, there is introduced evaluated accuracy of spatial data acquisition and comparison of computational cost generated programs.

Project shows calibration stereoscopic sensor. Also describes basic methods stereo-corespodation using library OpenCV. Project contains calculations of disparity maps on CPU or graphic card(using library OpenCL).

Project shows calibration stereoscopic sensor. Also describes basic methods stereo-corespodation using library OpenCV. Project contains calculations of disparity maps on CPU or graphic card (using library OpenCL).

This thesis describes the design and workflow of creating an image processing application in Android system, and what are the possibilities in choosing development environment and how to implement them. Then I am writing about my solutions of creating applications, graphical user interface and an interface for Android. I am describing my approach in the design and functionality of the application, communication with the camera, storing and retrieving data. Further I explain which algorithms were implemented for image processing and image evaluation. Product of this thesis is a functioning application that allows to its user to capture images and video stream. The algorithm evaluates the entering data and shows the location of the number plate. The application also allows recognizing texts and numbers from images. There are other various practical features and options implemented within the application.

This thesis describes the design of the image processing for Android system, consisting of the choice of the development environment and its implementation. Workflow solution to the problem involves development of the Androidapplication and it’s graphical user interface. The text includes description of the application functionality, communicationwith a camera, storing and retrieving data. It also describes used algorithms and image processing methods used for detecting values from the counter of the gas meter.

This work deals with development of an application for optical music recognition. This application is designed for mobile phones with Android operating system. The work includes a brief introduction to the problem and introduces some existing solutions. There are described methods for image processing and classification, which are used in final application. It also shows the design and implemenation of the final aplication, where used methods for detection and removal of staff lines, detection and processing of musical symbols and their classification are described. The evaluation of the final application and a summary of achieved results are shown in the end of this work.

This masters thesis describes possibilities and principles of gesture-based computer interface. The work describes general approaches for gesture control.  It also deals with implementation of the selected detection method of the hands and fingers using depth maps loaded form Kinect sensor. The implementation also deals with gesture recognition using hidden Markov models. For demonstration purposes there is also described implementation of a simple photo viewer that uses developed gesture-based computer interface. The work also focuses on quality testing and accuracy evaluation for selected gesture recognizer.

This master's thesis deals with acceleration of geometrical image transforms using the GPU and NVIDIA (R) CUDA TM architecture. Time critical parts of the code are moved on the GPU and executed in parallel. One of the results is a demonstrational application for performance comparison of both architectures: the CPU, and GPU in combination with the CPU. As a reference implementation, there are used highly optimized routines from the OpenCV library, made by the Intel company.