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Cell segmentation using convolutional neural networks
Hrdličková, Alžběta ; Chmelík, Jiří (referee) ; Vičar, Tomáš (advisor)
This work examines the use of convolutional neural networks with a focus on semantic and instance segmentation of cells from microscopic images. The theoretical part contains a description of deep neural networks and a summary of widely used convolutional architectures for image segmentation. The practical part of the work is devoted to the creation of a convolutional neural network model based on the U-Net architecture. It also contains cell segmentation of predicted images using three methods, namely thresholding, the watershed and the random walker.
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Image segmentation using machine learning
Matějek, Libor ; Frýza, Tomáš (referee) ; Bravenec, Tomáš (advisor)
This work deals with machine learning and its application in the field of image segmentation and object recognition. The thesis describes the basic terminology related to machine learning and data related to it. It also focuses on the biological nature of the neuron and its technological applications. The basic types of neural networks and the key convolutional neural network for image processing are described. The work also presents the used architectures of convolutional neural networks. Then follow the methods of image preprocessing before the convolutional network R-CNN. Subsequently, some of the datasets suitable for image recognition are analyzed. The implementation is then realized in Python with support for the PyTorch framework from Facebook.
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Object tracking in video sequences
Libiš, Zdeněk ; Zukal, Martin (referee) ; Číka, Petr (advisor)
This thesis deals with object tracking in video sequence. It focuses on studying of one object´s motion in static background. Motion is defined by its direction and its speed. It was created 3 operators in RapidMiner to determine it. The operator called AccumulativeDifferenceImage searches a trajectory of motion by technique of accumulative difference image. Operator called OpticalFlow is created to describe type of motion and to find size of location´s transition. The operator called SpeedMeasuing is used for determining of speed, it calculates speed of object by using input´s binary masks in meters by second. In theoretical part of thesis are described the types of segmentation´s methods, basic types of block matching algorithms, attributes of video sequences and problem of recording of motions. In practical part are described implementations of every operator, the testing video sequences and showed results of tests for every operator.
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Detection of biological structures in TEM microscope images
Cikánek, Martin ; Chmelík, Jiří (referee) ; Potočňák, Tomáš (advisor)
The aim of the first part of this thesis is to explain the theoretical basis of transmission electron microscopy and to mention fundamental parts of transmission electron microscopes. The next part of this work is focused on possible methods of image segmentation, the use of neural networks in the detection of objects in an image and the subsequent clustering of results. The theoretical part of the thesis is concluded with an explanation of some already published methods of automatic detection of biological structures in microscopic images and theoretical design of the algorithm, which will be subsequently developed. The process of training neural networks in order to automatically detect biological structures in an image is described at the beginning of the practical part. This is followed by an evaluation of the results achieved by these networks. Subsequently, cluster analysis methods are applied to these results, the products of which are compared with each other and also with the results obtained by already published methods.
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Advanced picture segmentation for 3D view
Baletka, Tomáš ; Fliegel, Karel (referee) ; Boleček, Libor (advisor)
The thesis advanced image segmentation for 3D image deals with segmentation and anaglyph 3D views. In the theoretical part of the thesis describes the different approaches were used to image segmentation and closely related methods of image processing. In the following practical part was the implementation of selected methods and created user-friendly applications. The main objective of the program is to identify significant objects in the image. For the purpose of segmentation methods have been implemented based on k-means method, the method of contour and the growth of seeds. The program is created in Visual Studio 2008 and written in C + +. The input and output is the image in various formats (JPG, BMP, TIFF).
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Tissue characterisation in spectral CT data
Poláková, Veronika ; Jan, Jiří (referee) ; Jakubíček, Roman (advisor)
This bachelor thesis deals with tissue characterisation in virtual monoenergetic images (VMI). Firstly, literature survey presents spectral CT which allows reconstructing VMI. Secondly, statistical evaluation of tissue CT numbers was made for all energies of VMI which were reconstructed. It was found that with growing energy of VMI CT number increases or decreases with different steepness depending on a type of tissue. As a consequence, the suitable VMI offer better contrast resolution between selected pairs of tissues, which enables better tissue segmentation and classification in these images.
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Image Segmentation Using Height Maps
Moučka, Milan ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This thesis deals with image segmentation of volumetric medical data. It describes a well-known watershed technique that has received much attention in the field of medical image processing. An application for a direct segmentation of 3D data is proposed and further implemented by using ITK and VTK toolkits. Several kinds of pre-processing steps used before the watershed method are presented and evaluated. The obtained results are further compared against manually annotated datasets by means of the F-Measure and discussed.
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Image segmentation on GPU
Bravenec, Tomáš ; Mego, Roman (referee) ; Frýza, Tomáš (advisor)
Bachelor thesis is focused on using graphical processing units for parallel data processing, specifically on image processing. Main focus of this thesis is determining time difference in image processing using graphical processing unit and classic approach on processor. Another focus is accessing webcam and processing of captured frames.
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Minidarpa robot - visual navigation
Groulík, Tomáš ; Burian, František (referee) ; Kopečný, Lukáš (advisor)
Master`s thesis is focused on mobile robotics and computer vision. There is briefly introduced a library of functions for image processing OpenCV. Then it deals with image processing and navigation of mobile robots using image data. There are described segmentation methods and methods for navigating through feature points.
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Topology Recognition from Crossroad Plan
Huták, Petr ; Bartík, Vladimír (referee) ; Kreslíková, Jitka (advisor)
This master‘s thesis describes research, design and development of system for topology recognition from crossroad plan. It explains the methods used for image processing, image segmentation, object recognition. It describes approaches in processing of maps represented by raster images and target software, in which the final product of practical part of project will be integrated. Thesis is focused mainly on comparison of different approaches in feature extraction from raster maps and determination their semantic meaning. Practical part of project is implemented in C# language with OpenCV library.
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