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Implementation of wavelet transform in C++
Valouch, Lukáš ; Hasmanda, Martin (referee) ; Beneš, Radek (advisor)
The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.
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Utilisation of shape analysis methods for object classification in medical images
Karela, Jiří ; Odstrčilík, Jan (referee) ; Chmelík, Jiří (advisor)
Bachelor thesis deals with problems of shape analysis. It describes some procedures and methods related to this kind of analysis. The thesis is divided into theoretical part, practical part and conclusion. In the theoretical part we describe in greater detail some methods, with the help of which the practical part was solved. But other theories related to the topic are also described. The practical part then follows the given theory and solves the problem of shape analysis due to the knowledge gained in the theory. The algorithm is tested on medical data from CT of vertebrae. The conclusion serves as a summary and evaluation of the shape analysis solution. It also serves as a reflection on the realization of our method, ie how our solution and result could be improved.
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Firearm Type Identification in an Image
Čech, Ondřej ; Drahanský, Martin (referee) ; Dvořák, Michal (advisor)
Main goal of this work is to design, implement and test an approach for classifying firearms in an image into categories with short and long fireams, and then with single shot, multi-barreled, repeating and semi-automatic/automatic firearms. This problem was solved using SVM classifier together with Harris corner detector, FREAK descriptor and Bag of Words method. Accuracy of final program is up to 13,3 %.
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Image watermarking in frequency domain
Štrbíková, Tatiana ; Rajmic, Pavel (referee) ; Číka, Petr (advisor)
This thesis analyze digital watermarking. At first we can read about watermarking in generally. Secondarily, it considers about possibilities of watermarking, therefore about different ways of watermarking. Methods of digital watermarking we can divide into three main categories: spatial domain watermarking, frequency domain watermarking and spread spectrum watermarking. In detail there is described frequency domain watermarking. Two methods are compared. First method, which use DCT (Discrete cosine transformation) and second metohd, which use DWT (Discrete wavelet transformation). Finally we can found out, which method seems to be better.
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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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