National Repository of Grey Literature 68 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Methods for biomedical image signal segmentation
Krumpholc, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work deals with methods of segmentation of biomedical image signals. It describes, sums up and compares representative methods of digital image processing. Segmentation based on parametric representation is one of the mentioned methods. So as the basic parameter can be chosen for example luminance and the final binary image is obtained by thresholding. Next described method is segmentation based on edge representation. This method can be divided into edge detection by the help of edge detectors and of Hough transformation. Edge detectors work with the first and second derivation. The following method is region-based segmentation, which can be used for a image with noise. This category can be divided into three parts. The first one is segmentation via splitting and merging regions, when the image is split and the created regions are tested on a defined condition. If the condition is satisfied, the region merges and doesn’t continue splitting. The second one is region growing segmentation, when adjacent pixels with a similar intensity of luminance are grouped together and create a segmentated region. Third one is watershed segmentation algorithm based on the idea of water diffusion on uneven surface. The last group of methods is segmentation via flexible and active contours. Here is described an active shape model proceeding from a possibility to deform models so that they match with sample shapes. Next I also describe method Snakes, where occurs gradual contour shaping up to the edge of the object in the image. For the final editing is used mathematical morphology of segmentated images. I aimed to meet methods of image signals segmentation, to cover the chosen methods as a script in programming language Matlab and to check their properties on images.
Creating 3D Model of Temporomandibular Joint
Šmirg, Ondřej ; Bartušek, Karel (referee) ; Liberda,, Ondřej (referee) ; Smékal, Zdeněk (advisor)
The dissertation thesis deals with 3D reconstruction of the temporomandibular joint from 2D slices of tissue obtained by magnetic resonance. The current practice uses 2D MRI slices in diagnosing. 3D models have many advantages for the diagnosis, which are based on the knowledge of spatial information. Contemporary medicine uses 3D models of tissues, but with the temporomandibular joint tissues there is a problem with segmenting the articular disc. This small tissue, which has a low contrast and very similar statistical characteristics to its neighborhood, is very complicated to segment. For the segmentation of the articular disk new methods were developed based on the knowledge of the anatomy of the joint area of the disk and on the genetic-algorithm-based statistics. A set of 2D slices has different resolutions in the x-, y- and z-axes. An up-sampling algorithm, which seeks to preserve the shape properties of the tissue was developed to unify the resolutions in the axes. In the last phase of creating 3D models standard methods were used, but these methods for smoothing and decimating have different settings (number of polygons in the model, the number of iterations of the algorithm). As the aim of this thesis is to obtain the most precise model possible of the real tissue, it was necessary to establish an objective method by which it would be possible to set the algorithms so as to achieve the best compromise between the distortion and the model credibility achieve.
Using the Kinect sensor in detection of people
Janás, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
Bachelor thesis deals with the methods of people detection by using Microsoft Kinect. Depth image captured by this device is further processed by using standard algorithms from freely available OpenCV library. All of image processing methods are described in detail of their function and influence to image. The practical part of the work is focused on the realization of a simple program, which is serving for image segmentation and finding people.
3D shape from MRI
Menclík, Tomáš ; Smékal, Zdeněk (referee) ; Šmirg, Ondřej (advisor)
The main aim of the thesis is the reconstruction of three-dimensional surface from a~set of two-dimensional images. For the implementation of this application the programming language Java and its extension, that allows work with three-dimensional models, were chosen. First, viewing of three-dimensional models of two different file formats was necessary to allow. To create the three-dimensional models, the Marching Cubes algorithm was used. This algorithm is decribed theoretically in the text, description of the implementation and correction of deficiencies follows. Finally, the implementation of the inversion procedure of reconstruction of the three-dimensional surface, which is the extraction of two-dimensional images from the three-dimensional model, is described.
Processing of X-Ray images in studying jawbone diseases
Kabrda, Miroslav ; Šmirg, Ondřej (referee) ; Mikulka, Jan (advisor)
The subject of this thesis is a method proposed for automated evaluation of the parameters of X-ray of cystic disorders in human jawbones. The main problem in medical diagnostic is the low repeatability due to the subjective evaluation of images without using a tool for image processing. In this thesis are described the basic steps of image processing, various methods of image segmentation and chosen segmentation method live-wire. Selected segments were processed in the ImageJ Java environment. In the cystic regions their basic statistical and shape properties were evaluated. The obtained values were used for learning the classification model (decision tree) in the environment RapidMiner. This model was used to create a plug-in for automatic classification of the type of cysts in the program ImageJ.
Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
Detection of car approach speed using camera imge processing
Kovář, Jan ; Číka, Petr (referee) ; Šmirg, Ondřej (advisor)
The thesis deals with digital image processing, from the initial acquisition of digital picture frames, subsequent processing segmentation and algorithms to detect visual shapes on the scene. Image processing is a very broad topic, so here are analyzed for more understanding of the fundamental principles of perception and processing of video signals, image representation, his starting shooting through filters governing digital image processing methods to detect the objects in an image. It is also demonstrated by the size dependence of the object in the image on the distance from the camera, whereby we can determine the speed of approaching or moving away from the object. We will show you the specific determination of the distance we need to know the actual result size of the object. This is because the ratio between the size of the object depending on the distance is the same for each object. Finally, this work presents the resulting image frames for implementation using OpenCV library.
Human body detection in a video scene
Šmirg, Ondřej ; Číka, Petr (referee) ; Kohoutek, Michal (advisor)
The project consists of two distinct levels i.e. separation level and diagnostic level. At the separation level, statistical models of gaussians and color are separately used to classify each pixel as belonging to backgroung or foreground. Adopted method is mixture of gaussians.A mixture of gaussians model is suitable here because the results of the picture tests will not depend on the lens opening, but rather on the colors in the backgroung. A mixture of gaussians model for return data seems reasonable. The achieved results the used method on the real sequences are presented in the thesis. Diagnostic level is identified human body on the scene. Adopted method is ASM(Active Shape Models) with PCA(Principal Component Analysis). ASM are statistical models of the shape of human bodies which iteratively deform to fit to an example of the object in a new image.
DICOM protocol analysis and its utilisation in image signal processing
Valouch, Lukáš ; Přinosil, Jiří (referee) ; Šmirg, Ondřej (advisor)
This Bachelor thesis describes DICOM which is a summary of standards for handling, storing and transmitting information in medical imaging. This standard is developed by organizations ACR and NEMA, it is very large file and it contains 18 of documents which are an actual version of this norm. The last norm was got out in 2008. The most important part of this format of date and files is data image processing so called off-line communication. It follows description of implemented application in C, C++ languages by the help of Imebra library. This Imebra library is free in terms of license of GNU GPL. The resultant program is standard of DICOM from, which is described above. This program is concerned with imaging of 16 bits of dept on 8 bits of dept of display devices, for example common computer displays. This application is able to display several layers of DICOM’s pictures. Each of layers contains separated bites which are presented by importance of levels.
Comparison of 3D objects in JAVA language
Zapletal, Tomáš ; Smékal, Zdeněk (referee) ; Šmirg, Ondřej (advisor)
The main aim of the thesis is loading of 3D models in different file formats and its displaying, creating of slices from 3D models and vice versa making 3D models from slices, quantify inaccuracy of anti-aliasing and other formatting and investigate similarity of original and edited models. Everything in Java programming language and its extensions for 3D object tasks. Thesis builds on earlier project „3D shape from MRI“.

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