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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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Detection and Correspondence of Image Features
Hasmanda, Martin ; Kohoutek, Michal (referee) ; Říha, Kamil (advisor)
The main goal of this bachelor‘s thesis was obtain basic knowledge about image processing. Especially was this work specialized on features detection in images captured from different perspectives and for finding correspondences between those images. Preliminary were to be described the basic principles for understanding computer vision such as perspective projection, description model of the camera and two views geometry. From methods of the detection was introduced best-known and most widely used of the detectors Harris corner detector. He is independent of images rotation and he is analyzed in detail. Further was described SIFT detector, that is independent of images scale. In this work further be described to several methods for finding correspondences of images features. First were to be described and derived two basic transformation matrixes that arrange to the association with features of two images. The first homography matrix describes transformation of two 2D views and fundamental matrix. Fundamental matrix obtains from two images full information of captured 3D scene and projection matrixes of cameras. For to primary definition correspondences were to be used to methods SSD and NCC. These methods match correspondences after similarities surroundings of features. These methods unfiled correct assignment features. Therefore uses stochastic RANSAC algorithm. The RANSAC algorithm was in detail described in this work in basic form and further modified on MLESAC algorithm. This algorithm can find better correspondences than RANSAC. In the end was described simple application for implementation introduced methods.
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3D Reconstruction from two views
Myška, Milan ; Minář, Jiří (referee) ; Hasmanda, Martin (advisor)
This bachelor thesis deals with 3D reconstruction process using two 2D pictures of one scene taken with uncalibrated cameras. The first chapter focuses on mathematical theory behind this process. Epipolar geometry, locating keypoints method SURF, fundamental matrix, stereo rectification and stereo correspondence using block-matching method are explained here. The next chapter of my thesis describes a practical view of this topic and my own C++ program is introduced at the same time.
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Processing of fingerprints
Kazík, Martin ; Hasmanda, Martin (referee) ; Říha, Kamil (advisor)
This diploma thesis deals with the identification of persons by their fingerprints. In the beginning, there is a brief overview of biometric methods. The issue of fingerprints and their automatic processing is very extensive and addresses a large amount of literature. This work describes the various stages processing fingerprints from receiving a fingerprint scan through the methods of enhancing fingerprint, binarization, the detection of minutiae to compare two fingerprints. After a short introduction of biometric techniques is briefly introduced the history of fingerprints as an instrument for identification of persons. Subsequently, there is the description of problems of obtaining fingerprints from older methods that require the transmission medium, to methods of obtaining fingerprints directly into a digital format. There are described basic principles of sensors and the principle of their function. Next part deals with methods of processing digital fingerprint images. These are methods for fingerprint image enhancement, methods for image thresholding, thinning of ridge lines, detection of global and local characteristics of the fingerprint. The next section introduces the basic methods of comparison and classification of fingerprints. The practical part describes the specific implementation of fingerprint processing chain. For each processing stage is implemented one selected method. The result is an application that allows displaying the output of each phase, the comparison of fingerprints 1:1 and also finds a fingerprint in the database, by comparing one fingerprint with many.
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Installation and configuration of Octave computation cluster
Mikulka, Zdeněk ; Hasmanda, Martin (referee) ; Sysel, Petr (advisor)
This diploma thesis contains detailed design of high-performance cluster, primarely focused for parallel computing in Octave application. Each of component of this cluster is described along with instructions for installation and configuration. Cluster is based on GNU/Linux operating system and Message Parsing Interface. Design alllows implementation of this cluster in computers of schoolroom with active lessons.
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Processing of Stereoscopic Video Sequence
Hasmanda, Martin ; Šmirg, Ondřej (referee) ; Říha, Kamil (advisor)
The main goal of this master’s thesis was get up used methods for observation the stereoscopic scene with one couple of cameras and find out good solving for processing these resulting pictures for two-view and multiple-view autostereoscopic displays for three-dimensional perception. For methods for acquisition video was introduced two methods. They were method “Off-axis” with parallel camera axis and method “Toe in” with intersections axis. For fit method was choice the method named as “Off-axis“. It was not produces the vertical parallax and in detail was in this work described principle of this method. Further were describe principles off used methods for three-dimensional perception namely from the oldest method named anaglyph after methods for viewing at autostereoscopic displays. The Autostereoscopic displays were main goal of this thesis and so their principles were described in details. For production the result image for autostereoscopic displays was used generation intermediate images between left and right camera. Resulting videos were acquisition for testing scene in created in 3D studio Blender, where was possible setting system of cameras exactly parallel axis. Then were introduce principles processing video where was extract from the couple of cameras where were connected to PC for help digitizing card and next time with two web cameras. Here is not guaranteed exact parallel axis system. Therefore this work try for real cameras achieve exactly parallel axis system by the help of transformations of frames with stereo rectification. Stereo rectification was solving with OpenCV libraries and was used two methods. Both methods work from principles epipolar geometry that was described in this work also in detail. First method rectifies pictures on the basis fundamental matrix and found correspondences points in two images of the scene and second method rectifies pictures from knowledge intrinsic and extrinsic parameters of stereoscopic system of cameras. In the end of this work was described application for implementation introduced methods.
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