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Lossless Image Compression
Komjáthy, Gergely ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This thesis deals with lossless image compression. In this paper are shown some colour models, which can be used for lossless image compression and formulas how to convert them to RGB and vica versa. You can learn predictors, how they work and discription of some of them. There is described the function of arithmetic coder, PPM coder and a brief description of Huffman coding.
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Automatic image annotation
Hegmon, Jiří ; Karásek, Jan (referee) ; Burget, Radim (advisor)
Recognition and comparison of image is one of the main problems and area of the field of computer vision. This thesis adds to these two issues the third, the recognition image semantics, so called annotations or labels. This work uses the knowledge of methods of recognizing the similarity of images to create a tool that is able based on training dataset of images and annotations, create a group most likely annotation for the test set of images. This work presents several types of test datasets suitable for the detection of annotation information for images. Subsequently, best set with the necessary training dataset size and enough information about annotations is selected. Based on this training dataset algorithm is designed for easy loading test set without large demands on computer performance. Evaluation of annotation information is done based on different similarity algorithms. At the beginning of this work was to use a simple, but not very effective method of MSE and comparison of color histograms, but gradually it was necessary to move to using more advanced methods (such as Tamura, Gabor, CEDD nebo různé druhy hostistogramů). The results of this comparison are then taken to evaluate the likelihood of the annotation for the image specified test set. The last part is an evaluation of the accuracy of annotation based on information from the test set.
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The Analysis of Real Estate Agencies Perception
Peťa, Tomáš ; Gavlas, Ondřej (referee) ; Chalupský, Vladimír (advisor)
The diploma thesis is focused on the area of real estate agents. It deals with the analysis of awareness of the real estate offices with direct targeting on the real estate company Gaute a.s. It identifies the current situation on the real estate market and the respondents' satisfaction with the services offered. In the theoretical part, the reader is made familiar with key concepts related to the topic, followed by the analysis, which is composed of the performance of Gaute a.s. preparation questionnaire and evaluation. Based on the findings recommendations are proposed, which will serve to raise awareness of the real estate office.
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Objects Classification in Images
Gabriel, Petr ; Petyovský, Petr (referee) ; Janáková, Ilona (advisor)
This master's thesis deal with problems of classification objects on the basis of atributes get from images. This thesis pertain to a branch of computer vision. Describe possible instruments of classification (e.g. neural networks, decision tree, etc.). Essential part is description objects by means of atributes. They are imputs to classifier. Practical part of this thesis deal with classification of object collection, which can be usually found at home (e.g. scissors, compact disc, sticky, etc.). Analyzed image is preprocessed , segmented by thresholding in HSV color map. Then defects caused by a segmentation are reconstructed by morfological operations. After are determined atribute values, which are imputs to classifier. Classifier has form of decision tree.
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Digital Steganalysis
Molnár, Ondřej ; Nevoral, Jan (referee) ; Strnadel, Josef (advisor)
Steganalysis is the opposite science discipline of the steganography - which is an art of information hiding . Steganography deals with embedding of secret messages to different types of media. The most commonly used cover media in modern steganography are image files . This bachelor's thesis creates an overview of known steganograpy and steganalysis methods . It also describes practical implementation of application that is able to detect hidden information in image.
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Face detection and recognition with use of Raspberry Pi
Rozhoňová, Andrea ; Mézl, Martin (referee) ; Hesko, Branislav (advisor)
The following bachelor thesis is focused on the face detection and recognition in an image. The theoretical part divides methods of detection and recognition into several groups and there is better description and explanation of these methods in this part. At the end of the theoretical part is summarized the current utilization of person recognition on the bases of its face in practice. In the practical part is first implemented method for face detection. It is combination of two approaches - approach using haar features and approach using templates of eye. The face recognition is provided by the convolutional neural network. In conclusion there are summarized principles and problems associated with implementation on microcomputer Raspberry Pi and there is also evaluated the success of implemented methods.
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Automatic 3D segmentation of brain images
Bafrnec, Matúš ; Dorazil, Jan (referee) ; Kolařík, Martin (advisor)
This bachelor thesis describes the design and implementation of the system for automatic 3D segmentation of a brain based on convolutional neural networks. The first part is dedicated to a brief history of neural networks and a theoretical description of the functionality of convolutional neural networks. It represents a fast introduction to the problematics and provides theoretical basics needed for the understanding and creation of the system. Individual layers of the neural network and principles of their functionality and mutual relations are also described in this part. The second part of the thesis is about problem analysis, designing of a solution and a comparison between neural networks and other solutions. The result of a magnetic resonance imaging of the head is a series of black-and-white images representing a 3D scan. The task is to tag a brain and to remove unnecessary information in the form of surrounding tissues. The final image of the brain can be utilized in a volumetry or during a diagnostic of neurodegenerative diseases. The advantage of neural networks in comparison with deterministic systems is their flexibility. They allow an adaptation to other segmentation problems just by changing the training dataset, without a need of changes in the architecture. One of the systems performing fully automatic 3D segmentation is called U-Net – its name comes from the similarity of the architecture with the letter U. Three real solutions, the first implementation of U-Net, extended U-Net and recurrent U-Net were presented. The first version of U-Net has been very memory-demanding, it required a training on a processor instead of a graphic card and has not allowed data processing in full resolution. The extended U-Net has resolved these problems by loading data in overlaying series of three images. In addition to the possibility of a training on a graphic card with related decrease in learning time, the accuracy was increased by adding interconnections to the internal architecture of the network. The last version, recurrent U-Net, aims for the optimization of extended U-Net based on the reusage of existing levels. This brings a decrease in a time and resource difficulty. The number of parameters of the network was lowered to less than 20%, without any increase in case of further level addition. This network is one of first recurrent networks used on the problem of 3D segmentation and provides a foundation to further research. The last part focuses on the evaluation of results and the comparison of accuracy, speed and requirements between particular networks. The accuracy of human and machine segmentation is also compared. The extended and recurrent U-Net have surpassed their human opponent, which in real case could save a lot of doctors time and prevent human mistakes. The result of this work is a theoretical basis providing an introduction to the problematics of convolutional neural networks and segmentation, fully working systems for automatic 3D segmentation and the foundation for further research in the field of recurrent networks.
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HOUSE ON THE FOOTHILL - TOWN HOUSE IN THE HISTORICAL CENTRE
Veselá, Marie ; Rudiš, Viktor (referee) ; Oplatek, Jiří (advisor)
Potential sites lies not only in its location but also the dominant position it holds to their surroundings. Undeveloped plot represents a "node" or "island" ... loosening strictly linear character Bakery. It is a place which brings together three disparate streams - Classical serious at the running part of Mendel Square, dramatically quarreling upper section flowing into the area from Hus class and insignificant Anenská that, if there "just got lost." All "three" street, however, are closely connected with the plot and the transformation of space clearly indicates their transformation. A distinctive feature of the property is its visual exposure of looking from Mendel Square, the plot creates a "picture" to which the pawn closer. This image should be interesting, changing to attract one's attention for more than just one or two seconds. The image should not least communicate - what is happening on the ground, what links are individual objects ... a landmark and should, for use by infantrymen use. It should also not be attractive from a distance - when one zooms in close proximity, should be surprised by the discovery of something new, something that was not noticeable from a distance, it should be attention to detail, or idea that can be seen only at close contact.
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Software for Microscope Image Processing and Analysis
Pavlišta, Libor ; Odstrčilík, Jan (referee) ; Čmiel, Vratislav (advisor)
This project informs about the basic image processing on grayscale and binary images. The project deals with analyzing the data obtained. Acquaints with terms such as morphology and image segmentation. Acquired knowledge is applied to create a program to complete the processing of microscopic images in LabView programming environment with subsequent analysis and plotting of results into image. For a better idea supporting data about operation in progress are continuous images.
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