The aim of this diploma thesis is to design and implement a multiplatform application for detection, localization and determination of the extent of chronic wounds. The application is intended to assist nurses, doctors and healthcare assistants to monitor and evaluate chronic wounds in the course of treatment. The application is based on the Typescript programming language, on the Ionic hybrid application framework and on the Electron desktop application framework. Chronic wound assessment runs on the server-side where the Python programming language is used. The Flask application framework is used for the RESTful application interface and the OpenCV library is used for image processing.

The thesis deals with the processing and detection of specific objects in the image on the Android mobile platform. The main objective of this work was to design and then implement a mobile application for Android operating system, which allows control of pipetting processes based on images from a mobile device camera. The OpenCV library is used in the application for image processing. The resulting application should serve primarily in laboratories as a tool for complete analysis of the pipetting process. The work is divided into two main chapters, which further consist of sections and smaller subsections. The first chapter is devoted to the theoretical analysis of this work. Here is also describes used technology, Android operating system, OpenCV library and important parts of image processing. The second chapter deals with the proposal and subsequent practical solution of this work. There is a proposal and the following procedure for solving this work, important techniques, methods of processing and analysis of the camera image. The conclusion of the thesis is an evaluation of the results of the solution of this work.

This master thesis focuses on creating and processing a dataset, which contains semi-automatically processed images of vehicles licence plates. The main goal is to create videos and a set of tools, which are able to transform  input videos into a dataset used for traffic monitoring neural networks. Used programming language is Python, graphical library OpenCV and framework PyTorch for implementation of neural network.

The goal of this thesis is to design and implement a multiplatform multilingual mobile application for detecting leukocoria in an image of human face for iOS and Android platforms. Leukocoria is a whitish light of the pupil, which can be seen on the photo when the flash is used. Early detection of this symptom can save human eyesight. The application itself allows to analyze a user's photo and detect the presence of leukocoria. The goal of the application is to analyze eyes of the human, from which the mobile application name - Eye Check is derived. React Native framework was used to create a multiplatform mobile application. The Dlib library was chosen for human face and eye detection, the OpenCV library for working with the photo. The convolutional neural network was used to classify the eyes for the possible presence of leukocoria. Client-Server communication is solved using the REST architecture. The result is a mobile application that detects leukocoria and allerts the user to visit his doctor if leukocoria is detected.

This master's thesis focuses on smartphone game for iOS, which uses recognition of face features and other information, which can be obtained from a smartphone's camera and sensors. This work describes a few approaches for real-time face detection and then introduces and compares possibilities for such task on iOS. Moreover, the thesis contains a draft of the final game and its levels. The game showcases various technologies in its levels such as object detection, processing an image color and others. Finally, the thesis introduces the final form of the game that is released and available on the App Store.

This thesis deals with the design and subsequent implementation of a unit inspecting a printed logos on the pen surface. A line-scan camera is used to capture the object. Whole the unit including acquited data processing is controlled by Raspberry Pi 4 platform extended by perifery board. The control of the hardware parts is implemented in C++, the detection algorithms in Python using OpenCV and TensorFlow libraries. The unit has a graphical user interface for control of the inspection process. In the end of the thesis test of the unit reliability is shown.

The aim of this master's thesis thesis is to enable evaluation of quality, or the type of product in industrial applications using artificial neural networks, especially in applications where the classical approach of machine vision is too complicated. The system thus designed is implemented onto a specific hardware platform and becomes a subject to the final optimalisation for the hardware platform for the best performance of the system.

This thesis is focused on making application for mobile devices, which records progress of chess game. This is achieved by image recognition on input from camera. Chess figures are classified by neural network. Usage of application is during training or real matches to record games and then for analyzing these games. For analyzing, my application offers record in standard algebraic notation. User can also add notes to every game.

The aim of this thesis is to design and implement a toolchaning system for a 3D printer. As a consequence of such expansion, the printer gains the ability of multimaterial printing and switching between a number of active and passive tools during a single production process. In addition to extensive research of other currently available solutions, this thesis describes the complete mechanical and electrical design process of the device. It also documents the implementation of a functional sample, the creation of software both for the base system and the toolchanger expansion, and the implementation of an associated optical measurement and calibration system.

The thesis deals with design of a program for entering various types of geometric objects in an image for the purpose of their further processing. The program should also contain algorithms to ease object entering (e.g. refining manually entered object position). In the first part there is a brief description of the computer vision and its basic methods used in the work as well as introduction of the OpenCV image processing library. The following part describes three types of geometric primitives that are implemented for now. Because the output of the program is in universal XML format, there is short chapter about the XML. After that, there are summarized some methods for searching of parametric description of geometric primitives in an image. The final chapter describes the proposed system and evaluates possibility and suitability of its usage for various types of images.