|
|
Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
|
|
|
Analysis of Retinal Image Data to Support Glaucoma Diagnosis
Odstrčilík, Jan ; Kybic, Jan (referee) ; Matula,, Petr (referee) ; Kolář, Radim (advisor)
Fundus kamera je široce dostupné zobrazovací zařízení, které umožňuje relativně rychlé a nenákladné vyšetření zadního segmentu oka – sítnice. Z těchto důvodů se mnoho výzkumných pracovišť zaměřuje právě na vývoj automatických metod diagnostiky nemocí sítnice s využitím fundus fotografií. Tato dizertační práce analyzuje současný stav vědeckého poznání v oblasti diagnostiky glaukomu s využitím fundus kamery a navrhuje novou metodiku hodnocení vrstvy nervových vláken (VNV) na sítnici pomocí texturní analýzy. Spolu s touto metodikou je navržena metoda segmentace cévního řečiště sítnice, jakožto další hodnotný příspěvek k současnému stavu řešené problematiky. Segmentace cévního řečiště rovněž slouží jako nezbytný krok předcházející analýzu VNV. Vedle toho práce publikuje novou volně dostupnou databázi snímků sítnice se zlatými standardy pro účely hodnocení automatických metod segmentace cévního řečiště.
|
|
|
Advanced Image Edge Detection
Novák, Marek ; Nečas, Ondřej (referee) ; Španěl, Michal (advisor)
Edge detection is one of the fundamental techniques used in the fields of image processing and computer vision. Goal of this thesis is an implementation and evaluation of chosen basic and advanced edge detection methods, including performance evaluation. Thesis describes implementation and performance evaluation of Linked Edges as Stable Region Boundaries method. Performance is evaluated using Berkeley Segmentation Data Set and Benchmarks 500 .
|
|
|
Object Recognition by Neural Networks
Marák, Jaroslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is focused on neural networks and their classification capability in object recognition tasks. For recognition is there used neural networks with feedforward architecture which is learned by Back Propagation algorithm. We discusses about problems which appear while a choosing topology of network or using various lerning-significant parametters while a learning process. Achieved results are presented in experiments with estimation.
|
|
|
Free algebraic structures and their application for segmentation of a digital image
Čambalová, Kateřina ; Solovjovs, Sergejs (referee) ; Pavlík, Jan (advisor)
The thesis covers methods for image segmentation. Fuzzy segmentation is based on the thresholding method. This is generalized to accept multiple criteria. The whole process is mathematically based on the free algebra theory. Free distributive lattice is created from poset of elements based on image properties and the lattice members are represented by terms used by the threshoding. Possible segmentation results compose the equivalence classes distribution. The thesis also contains description of resulting algorithms and methods for their optimization. Also the method of area subtracting is introduced.
|
|
| |
|
|
Image Segmentation with Deep Neural Network
Pazderka, Radek ; Šůstek, Martin (referee) ; Rozman, Jaroslav (advisor)
This master's thesis is focused on segmentation of the scene from traffic environment. The solution to this problem is segmentation neural networks, which enables classification of every pixel in the image. In this thesis is created segmentation neural network, that has reached better results than present state-of-the-art architectures. This work is also focused on the segmentation of the top view of the road, as there are no freely available annotated datasets. For this purpose, there was created automatic tool for generation of synthetic datasets by using PC game Grand Theft Auto V. The work compares the networks, that have been trained solely on synthetic data and the networks that have been trained on both real and synthetic data. Experiments prove, that the synthetic data can be used for segmentation of the data from the real environment. There has been implemented a system, that enables work with segmentation neural networks.
|
|
|
Methods of deep learning in image processing tasks
Polášková, Lenka ; Marcoň, Petr (referee) ; Mikulka, Jan (advisor)
The clue of learning to recognize objects using neural network lies in imitation of animal neural network's behavior. In spite the details of how brain works is not known yet, the teams consisting of scientists from various medical or technical professions are trying to search for them. Thanks to giants like Geoffrey Hinton science made a big progress in this domain. The convolutional networks which are based on animal model of optical system can be advantageously used for image segmentation and therefore they ware chosen for segmentation of tumor and edema from images of magnetic resonance. The models of artificial neural networks used in this work had achieved the 41\% of success in edema segmentation and 79\% in segmentation of tumor from brain issue.
|
|
|
Road detection for mobile robot using image processing
Coufal, Jan ; Štarha, Pavel (referee) ; Krejsa, Jiří (advisor)
Diploma thesis deals with image processing for outdoor environment mobile robot. In first part, the problem is analyzed, general solution is proposed and suitable image processing methods are presented. In second part presented methods are tested and methods with best results are proposed. In third part is particular solution tested on real data.
|
|
|
Non-contact measurement of the dimensions of determination scales
Šemora, Petr ; Matoušek, Radomil (referee) ; Škrabánek, Pavel (advisor)
This thesis deals with non-contact measuring the dimensions of the sand lizard anal plate. First the thesis briefly summarizes the techniques used to measure object dimensions and the techniques used for image segmentation. Subsequently, the thesis provides a basic overview of neural networks and convolutional neural networks. The practical part describes a system for measuring the dimensions of the sand lizard anal plate. The proposed algorithms are implemented in a graphical user interface enabling automatic and manual measurements.
|
guest ::
