The master thesis deals with the topic of detecting faces in digital images. There are generally described and classified the most frequently used methods and discussed their advantages and disadvantages. More detailed is described skin color detection, eye and mouth detection and are teoretically described machine learning algorithms and detection based on Haar-classifiers. The work aims to implementation of these methods in the OpenCV library, it refers to practical application of them a finally compares different provided trained files.

This diploma evaluates methods for verification of key characteristics of a product using digital image processing techniques. At first, reasons why this work has been done are described followed by a list of all methods that were used in this diploma such as Hough Circle Transform and Flood Fill (Seed Fill) algorithm. Also, a new approach how to compensate non regularly illuminated scene, which is based on surface modeling with Bézier Surfaces, was developed. Moreover, the algorithm was implemented in the C++ programming language and some of the parts were also simulated using the MATLAB environment. The algorithm was evaluated based on the percentage level of recognition of the required parameters. Efficiency of the implementation is also important for the author.

Master`s thesis is focused on mobile robotics and computer vision. There is briefly introduced a library of functions for image processing OpenCV. Then it deals with image processing and navigation of mobile robots using image data. There are described segmentation methods and methods for navigating through feature points.

This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.

This work focuses on the theory of artificial neural networks: the history, individual ways of learning and architecture of networks. It is also necessary to desribe the image processing blocks from scanning and image processing through segmentation to object recognition. The next part is focused on connecting the previous two parts, and therefore on the use of neural networks in image processing, specifically the identification of objects. In the practical part of the work is designed the user application for recognizing characters such as numbers, uppercase and lowercase letters.

This master‘s thesis deals with the design and implementation of computer application for facial expression recognition. The first section describes the image processing, especially algorithms used in other parts of this thesis. The next section describes methods used for face detection, particularly the Viola-Jones detector. This is followed by a brief description of the basic facial expressions recognized by the application. The last two sections are dedicated to the design and implementation of the facial expression recognition algorithms and to the evaluation of the results.

This thesis presents the Deriche edge detector as an interesting alternative to the commonly used edge detectors. The Deriche edge detector's design is presented to the reader as well as its strengths and weaknesses. Performance issues of the Deriche edge detector are described in comparison with the Canny edge detector together with recommendations for using the Deriche detector. Finally, edge detection quality of the Deriche edge detector is compared to the Canny edge detector using robust subjective evaluation method.

This master's thesis deals with fire detection in videosequences. Attention is paid to the known characteristics of fire and basic principles of existing solutions which deal with this issue. The thesis also describes design, implementation and testing of a fire detector that is based on the recognition of suspicious areas by fire color modeling, combined with detection of motion and light intensity variations.

This project deals with monitoring cars approaching the crossroads. Describes various methods of detection and discussing their problems. Primary goal is surveillance during the day in different weather conditions, but method of detection cars during the night and low light is also introduced. The most widely used algorithms are implemented using the OpenCV library. Important part is testing different algorithms and also variety of lighting conditions, camera locations and settings.

This master thesis deals with the use of gestures in user interfaces. The goal of this thesis is to create library for hand tracking and gesture recognition in real time. For hand tracking was choosen algorithm Flock of Features. Classification of gestures is done by using algorithm DTW. This thesis also contains stage design, design and implementation of a system that uses this library. Within the tests was tested control of various application using this library.