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Automatic Construction of a Terrain Map by a Drone
Kapsa, Jan ; Bambušek, Daniel (referee) ; Beran, Vítězslav (advisor)
This thesis focuses on how UAV mapping functions with the focus on methods working in real-time. The process of image stitching is thoroughly explained and 2 methods based on it are designed. Together with these methods dataset is built containing different situations. Maps of the terrain are created by these methods, which are then compared and scored.
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Složení snímku prstu s viditelným krevním řečištěm.
Pekárek, Jakub ; Semerád, Lukáš (referee) ; Rydlo, Štěpán (advisor)
This thesis describes a method for creating a composite image with a visible bloodstream. The bloodstream is detected by the Maximum Curvature algorithm. After that it was experimented with detecting and matching keypoints via algorithms SIFT and ORB. However, the resulting matches from these algoritms were not good enough, therefore the keypoints have to be manually assigned. From these keypoints, an estimated tranformation matrix was created. This matrix was then used for connecting two images. A cycle of assigning keypoints and connecting images is repeated even for newly created images. The final composite image with a visible bloodstream is created after connecting last two images. This composite image can be further used for verification or identification people.
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Robot Localization Using Camera
Heřman, Petr ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
The objective of this work is to design a simple localization method and its implementation in robot operating system ROS. This method uses a monocular camera as the only sensor and estimates the position in a known map. In experiments with prototypes are tested key points of type SURF, SIFT and ORB.
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Merging and Correction of Photos
Trčka, Jan ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
The aim of this work is to design and implement an application using an OpenCV library. This paper describes issues of correct photo merging, attempts to eliminate defects which were created in process of taking these photos and which may occur in the actual merging process.
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Detection algorithms of moving objects
Novotný, Josef ; Mikulka, Jan (referee) ; Marcoň, Petr (advisor)
This work deals with detection methods of moving objects. This thesis contains a research of available solutions for further implementation on the Raspberry Pi using the OpenCV library. The aim of the thesis is to realize a module that is capable of detecting and recognizing moving objects in the sky. Required objects can be detected in static or dynamic mode. In the theoretical part of the thesis are methods divided into motion detection, object detection and object recognition. In the practical part were for detection of undesired objects selected a background subtraction method and the localization of significant ORB points. Haar feature-based cascade classifiers was for recognition of learned objects chosen. In the practical part, methods were of computational difficulty and detection success tested. The result is an automatic detection device that allows to watch and distinguish unwanted objects in the sky.
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Merging of Images and Video Sequences
Krym, David ; Seeman, Michal (referee) ; Zemčík, Pavel (advisor)
This bachelor thesis deals with image and video sequence frames stitching when the camera undergoes a pure rotation. It involves design and implementation of application with focus on quality and performance. Modern techniques and algorithms are used, such as SURF, ORB, k-nearest neighbors and bundle adjustment. The application is able to create a panoramic images automatically without any assumptions about the scene or camera.
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Automatic image classification
Ševčík, Zdeněk ; Miklánek, Štěpán (referee) ; Sikora, Pavel (advisor)
The aim of this thesis is to explore clustering algorithms of machine unsupervised learning, which can be used for image database classification by similarity. For chosen clustering algorithms is written up a theoretical basis. For better classification of used database this thesis deals with different methods of image preprocessing. With these methods the features from image are extracted. Next the thesis solves of implementation of preprocessing methods and practical application of clustering algorithms. In practical part is programmed aplication in Python programming language, which classifies the database of images into classes by similarity. The thesis tests all of used methods and at the end of the thesis is processed searches of results.
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Region Detectors and Descriptors in Image
Žilka, Filip ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis deals with an important part of computer vision field. Main focus of this thesis is on feature detectors and descriptors in an image. Throughout the thesis the simplest feature detectors like Moravec detector will be presented, building up to more complex detectors like MSER or FAST. The purpose of feature descriptors is in a mathematical description of these points. We begin with the oldest ones like SIFT and move on to newest and best performing descriptors like FREAK or ORB. The major objective of the thesis is comparison of presented methods on licence plate localization task.
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