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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.
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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.
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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.
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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.
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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.
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Multiple Object Tracking
Takács, Ákos ; Drahanský, Martin (referee) ; Rozman, Jaroslav (advisor)
This paper is focusing on technical specification, concept and implementation of multiple object tracking with using a standard web camera. Image data processing has been done through the OpanCV library. The system is able to rotate the camera, in order to have the chosen target in the center of the screen. FITkit controller has been used to control the camera. The software has been implemented in the C++ environment.
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Autonomous vehicle for traffic situation model
Schneiderka, Dominik ; Boštík, Ondřej (referee) ; Janáková, Ilona (advisor)
This thesis describes development of autonomous car for Carrera 143 racing track. Main objective of a car is to stop when traffic light shows red, or when there is an obstacle infront of a car. This paper also describes electric schemes used to control the car and their placement on the car. Algorithms developed for image processing are developed for processing unit Raspberry Pi Zero and are written in C/C++ programming language. OpenCV library is used for image processing. All source codes were developed in Microsoft Visual Studio 2019.
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Real-Time Image Processing Algorithm Implementation
Rypák, Andrej ; Zemčík, Pavel (referee) ; Černocký, Jan (advisor)
This Bachelor's Thesis was performed during a study stay at the École Supérieure d'Ingénieurs en Électronique et Électrotechnique Paris, France. In this project, I deal with designing program components for a rapid prototyping software called SynDEx that is used for automatic code generation, real-time application development and optimization for multicomponent mixed architectures. I briefly introduce this software. I present techniques I used to implement two different specific image processing chains and a displaying component. The chains perform image segmentation and labelling.In this project I deal with designing program components for a rapid prototyping software called SynDEx that is used for automatic code generation, real-time application development and optimization for multicomponent mixed architectures. I briefly introduce this software. I present techniques I used to implement two different specific image processing chains and a displaying component. The chains perform image segmentation and labelling.
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Automatic detection of microcalcifications in mammogram images
Hývlová, Denisa ; Jakubíček, Roman (referee) ; Harabiš, Vratislav (advisor)
This bachelor thesis is focused on detection of microcalcification in mammography images. The introduction describes connection between their presence and breast cancer, principle of mammography and the DICOM standard used in radiology. In the following part the methods used for microcalcification enhancement and segmentation are explained. Detection algorithm based on wavelet transform, morphological closing and thresholding was designed in MATLAB. For evaluation of the results a graphical user interface was developed and an algorithm for automatic evaluation of the success rate in annotated mammography database was implemented.
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