|
QR code detection using deep learning
Černohous, Matěj ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis deals with the design of an algorithm for detecting and decoding QR codes in images using deep learning techniques. The work involved the construction of 2 datasets, a YOLOv7 neural network model for detecting QR codes in images, a YOLOv4-tiny neural network model for detecting position markers of QR codes, and a Python program utilizing these models to read QR codes in images. For evaluation, the algorithm was compared with other options for QR code reading.
|
|
Intracranial hemorrhage localization in axial slices of head CT images
Kopečný, Kryštof ; Chmelík, Jiří (referee) ; Nemček, Jakub (advisor)
This thesis is focused on detection of intracranial hemorrhage in CT images using both one-stage and two-stage object detectors based on convolutional neural networks. The fundamentals of intracranial hemorrhage pathology and CT imaging as well as essential insight into computer vision and object detection are listed in this work. The knowledge of these fields of studies is a starting point for the implemenation of hemorrhage detector. The use of open-source CT image datasets is also discussed. The final part of this thesis is a model evaluation on a test dataset and results examination.
|
|
Speed Measurement Using Radar
Andrla, Jiří ; Široký, Adam (referee) ; Maršík, Lukáš (advisor)
The principal goal of this bachelor thesis is to design a program in the Matlab programming language that measures the speed of vehicles scanned by a radar. In this thesis, the program is also implemented in the C++ programming language. The designed software detects moving vehicles in sets of data obtained from a CW radar. For each of these vehicles, their speed is computed with respect to the angle of their motion to the orientation of the measuring device. In the end, overall statistics are generated from the data gained. The thesis solves the problems of correction of the speed measurement based on the measuring angle. This technique should provide better results than other classical methods without the correction. The outcome of this thesis can be interesting for every application or system that uses speed measurement with a radar under different angles.
|
|
Detection of cells in confocal microscopy images
Hubálek, Michal ; Štursa, Dominik (referee) ; Škrabánek, Pavel (advisor)
The goal of the thesis was to create an application that automatically detects healthy cardiomyocytes from images captured by a confocal microscope. The thesis was created based on the specific needs of researchers from the Slovak Academy of Sciences.The application will facilitate and increase the efficiency of their research,because until now they have to evaluate the images and search for suitable cells manually. The RetinaNet convolutional neural network is used for detection and has been implemented in a user-friendly desktop application. The application also automatically records and stores coordinates of detected cells which can be used for capturing cells in higher image quality. Another advantage of the developed application is its versatility, which allows to train detection on other data, making it applicable to other projects. The result of this work is a functional, standalone and intuitive application that is ready to be used by researchers.
|
|
Board Game User Interface with a Camera
Cihlářová, Dita ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
Cílem této práce je vytvořit systém, který bude schopen nahradit reálného protihráče ve hře Dostihy a sázky. Hra je snímána kamerou, ze které se obraz přenáší do počítače, kde probíhá zpracování obrazu a identifikace herních objektů. Dále aplikace analyzuje stav hry a rozhodne o svém následujícím tahu. Rozhodovací algoritmus je schopen reagovat na každou herní situaci a tudíž dohrát hru do konce. Aplikaci mohou využít hráči, jež rádi hrají Dostihy a sázky, ale chybí jim protihráč. Aplikace také může najít uplatnění jako demostrace možností počítačového vidění.
|
|
Detection of multiple objects using computer vision
Maršala, Štěpán ; Škrabánek, Pavel (referee) ; Parák, Roman (advisor)
The aim of the bachelor's thesis is designing and realizing an algorithm for different shapes, colors, and sizes object detection. The paper is divided into five chapters. The first chapter includes introduction to so far developed computer vision. The second chapter describes functions and uses of open source library OpenCV, which is used in practical part of this paper. Practical part begins with chapter which covers all used hardware and technology. Next chapter describes task of separating objects. Further are included all technical aspects and problem solutions. In last chapter is a report about practical work realization in laboratory. Summary of all experiment results and paper cognition is in conclusion of the paper.
|
|
Detection of cellular processes in image sequences
Hatrinh, Hung Anh ; Richter, Miloslav (referee) ; Petyovský, Petr (advisor)
Překlad abstraktu (Tato bakalářská práce se zabývá segmentací buněk od obrazového pozadí a detekcí buněčných procesů v kvantitativních fázových obrazech získaných koherencí řízeným holografickým mikroskopem. Navržený algoritmus na segmentaci buněk využívá hranového detektoru watershedingu. Implemtován byl v programovacím jazyce C++ a využívá knihovny OpenCV. Detekce buněčných procesů je řešena metodami strojového učení v MATLABu.)
|
|
Online interest point detector
Přibyl, Jakub ; Rajnoha, Martin (referee) ; Mašek, Jan (advisor)
This thesis focuses on online learning detector for long-term tracking of object in video sequence. The object is defined by a bounding box. The text describes different parts of the detector: object tracking, object detection and online learning detector. The main contribution of this work is creating extension of the OpenTLD program for parallel detection and tracking of multiple objects. The parallelization is then compared on two practical examples and the processor's impact on detection is compared. The best results were achieved with parallelization, where all objects were detected. The most accurate detection was in the case of sufficiently learned objects with the smallest shape change.
|
|
Object Detection and Tracking Using Interest Points
Bílý, Vojtěch ; Hradiš, Michal (referee) ; Juránek, Roman (advisor)
This paper deals with object detection and tracking using iterest points. Existing approaches are described here. Inovated method based on Generalized Hough transform and iterative Hough-space searching is proposed in this paper. Generality of proposed detector is shown in various types of objects. Object tracking is designed as frame by frame detection.
|
|
Object Detection and Recognition in Image
Muzikářová, Michaela ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
This bachelor's thesis deals with design and implementation of client-server application for object recognition with the use of existing mobile application. Theoretical part describes the differences between human and computer vision, followed by information about object detection and recognition with selected methods. The next section provides a detailed overview of artificial neural networks, which were used for this work, with their qualities for object recognition. Following part examines selected mobile applications for object recognition, followed by existing frameworks and libraries with focus on artificial neural networks. Among these, Caffe Framework was selected for the work. The next section illustrates the progress of design and implementation and describes the system, along with experiments and dataset used to prove its functionality.
|