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Object Detection Based on Edges
Caha, Jaroslav ; Švub, Miroslav (referee) ; Španěl, Michal (advisor)
This work presents a door detection method in images for mobile robot navigation. The method is able to detect doors in an input picture on the basis of found image edges. It is important to distinguish the door from similar objects like windows, paintings, or floor patterns. Therefore, the picture is divided into more parts (a floor, a wall, a ceiling) so that the potential placement of the door can be better drawn.
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System for Augmented Reality Utilisation in Museums and Galleries
Müller, Frederik ; Šolony, Marek (referee) ; Beran, Vítězslav (advisor)
The aim of the master thesis is to provide visitors of various types of objects - typically galleries, museums, etc. with additional information about exhibited objects with emphasis on visual display in augmented reality. It includes an analysis of already existing solutions, design and implementation of the entire system needed for deployment. From the point of view of the content creator (administrator), the system represents a complex solution enabling the creation of an interactive walk - scanning 3D objects, scanning 2D objects and adding content to the given objects. On the other hand, the tool for visitors (users) who are part of an interactive walk, provides additional information about objects primarily located near the user, which are automatically detected by the camera on the mobile phone. Solution includes augmented reality, which is implemented using ARKit technology, so the final application is built on the iOS platform. The work addresses the issue of detection of 3D objects and their subsequent recognition, along with the way to work with this information, how to store it and then use it for purposes of this thesis. In the final solution, emphasis is placed on the simplicity of the usage (guide marks, hints...) and overall user experience.
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Image processing and depth maps to create an interactive model
Gelo, Lukáš ; Adámek, Roman (referee) ; Appel, Martin (advisor)
This bachelor’s thesis deals with creation of communication protocol for Intel® RealSense™ cameras in MATLAB, creation of program which finds certain objects in image using depth map and implementation of this program into mechatronic exponate. Theoretical part deals with methods of depth and distance scanning. It clarifies principles of contactless and nondestructive measurement of depth and distance along with comparison of their advantages and disadvantages.
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Object Detection in Video Sequences
Šebela, Miroslav ; Beneš, Radek (referee) ; Číka, Petr (advisor)
The thesis consists of three parts. Theoretical description of digital image processing, optical character recognition and design of system for car licence plate recognition (LPR) in image or video sequence. Theoretical part describes image representation, smoothing, methods used for blob segmentation and proposed are two methods for optical character recognition (OCR). Concern of practical part is to find solution and design procedure for LPR system included OCR. The design contain image pre-processing, blob segmentation, object detection based on its properties and OCR. Proposed solution use grayscale trasformation, histogram processing, thresholding, connected component,region recognition based on its patern and properties. Implemented is also optical recognition method of licence plate where acquired values are compared with database used to manage entry of vehicles into object.
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Graphics and Video Algorithms in GP-GPU
Kula, Michal ; Polok, Lukáš (referee) ; Zemčík, Pavel (advisor)
This diploma thesis is focused on object detections through general-purpose computing on graphics processor units. There is an explanation of graphics adapters work and basics of their architecture in this thesis. Based on the adapters, there is the effective work in libraries for general-purpose computing on graphics processor units demonstrated in this thesis. Further, the thesis shows the available algorithms for object detection and which ones from them are possible to be effectively parallelized. In conclusion of this thesis, there is a comparison of the object detections speeds to common implementations on classical processors.
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Augmented Reality for Commercials
Angelov, Michael ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Master's thesis presents a possible application of augmented reality in domain of commerci- als. It presents designed architecture of a mobile application that is able to detect and track specific objects (e.g. printed commercials, logos) in mobile';s phone camera in real time and provide some extra information about the detected object towards the user. Thesis also provides a review of contemporary used techniques in object recognition, object tracking and image retrieval from image databases.
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Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
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Hand Extraction from a Photo with Different Backgrounds
Kováčik, Timotej ; Kanich, Ondřej (referee) ; Sakin, Martin (advisor)
This thesis focuses on extraction of human hand from photographs with different backgrounds. The goal is to design and implement an algorithm capable of locating human hand in the image and identifying its parts. It analyses the methods of biometric identification and verification, methods used for extracting objects from an image. The outcome of this thesis is a design and implementation of an algorithm that is able to extract human hand from a photo and identify its parts.
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Pattern recognition by means of moment method
Števček, Juraj ; Štarha, Pavel (referee) ; Druckmüller, Miloslav (advisor)
This diploma thesis deals with object recognition using moment method. We will recognize the letters from the scanned text. The moment method works with principal moments, these are moments invariant to scaling, translation and rotation. This thesis focuses on a detail description of the moment method, on determining the optimal combination of principal moments suitable for object recognition and to create a program for recognition. For all combinations of principal moments the accuracy of the recognition is calculated and the best option is proposed. The moment method will be compared with the moment invariants method. This method is similar to the moment method but has a different approach to rotation invariants.
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Passive optical detection and classification of flying objects
Mošková, Andrea ; Marcoň, Petr (referee) ; Vlachová Hutová, Eliška (advisor)
Based on an initial analysis of the methods used for optical detection and recognition of moving elements in a dynamic image captured by a static camera, the bachelor's thesis presents a proposal for a complex detection algorithm capable of recording and classifying flying objects in the sky. The method uses a differential detection algorithm to detect signs of motion, thanks to which flying objects are located in the video frames. The SVM classifier then decides on the classification of the object into one of the three considered classes, based on its description obtained by extraction of SIFT descriptors and possibly supplemented with information from RGB histograms. The algorithm was implemented primarily in Matlab.
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