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Segmentation of important structures in retinal images
Trojánek, Václav ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis focuses on the segmentation of significant structures in retinal image data to improve the diagnosis and treatment of ocular diseases. Methods of retinal image analysis are investigated and implemented in this thesis. The thesis begins with an overview of the anatomy of the eye and the principles of background eye imaging using a fundus camera and an experimental video ophthalmoscope. This is followed by a detailed literature search focusing on current methods for the detection and segmentation of diagnostically important structures such as the optic disc, macula and blood vessels. A key part of the work is the implementation and testing of selected algorithms, including Hough transform for optic disc detection and OTSU thresholding for blood vessel segmentation and yellow spot detection based on previous optic disc segmentation.
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Image object detection
Pluskal, Richard ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
The thesis deals with design of a program for entering various types of geometric objects in an image for the purpose of their further processing. The program should also contain algorithms to ease object entering (e.g. refining manually entered object position). In the first part there is a brief description of the computer vision and its basic methods used in the work as well as introduction of the OpenCV image processing library. The following part describes three types of geometric primitives that are implemented for now. Because the output of the program is in universal XML format, there is short chapter about the XML. After that, there are summarized some methods for searching of parametric description of geometric primitives in an image. The final chapter describes the proposed system and evaluates possibility and suitability of its usage for various types of images.
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3D Objects Reconstruction from Image Data
Cír, Filip ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This paper deals with 3D reconstruction of objects from image data. There is describes theoretical basis of the 3D optical scanning. Handheld 3D optical scanner setup is described composed of a single camera and a line laser whose position is fixed with respect to the camera. Set of image markers and a simple real-time detection algorithm are proposed. Detected markers are used to estimate position and orientation of the camera. Finally, laser detection and triangulation of points lying on object surface are discussed.
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Hough's transform for circle detection
Kazík, Martin ; Burget, Radim (referee) ; Říha, Kamil (advisor)
The thesis is focused on the implementation of Hough transform algorithm for circle recognition. Algorithm is implemented in C++ language using open source library OpenCv. As a development environment was chosen Microsoft Visual Studio 2008. At first there is general description of classical Hough transform for line and circle recognition. Then thesis contains description of particular steps of Hough transform algorithm and description of OpenCv functions witch are used in these steps. There is a detail description of functions for converting image to grayscale, smoothing image by Gaussian filter and Canny edge detector for edge detecting in smoothed image. Efficiency and speed of algorithm is increased by using function for finding possible centers. This function using the fact that line perpendicular to the chord of circle and going thought its middle point at the same time have to cross the center of the circle. Results of particular stages of algorithm (converting to grayscale, smoothing by Gaussian filter, edge detection, creating of possible centers accumulator and drawing circles) are presented on ultrasonic image of collagen arterial substitute. In the second part of the thesis the algorithm is used for detection of artery in frames of video captured by ultrasound. There is a description of automatic method for evaluating of success of artery detection. Success of detection is analyzed by changing values of important algorithm parameters. From series of tests there are defined ideal parameters of algorithm for artery detection in the video.
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Line tracking for delivery robot
Juhas, Miroslav ; Horák, Karel (referee) ; Janáková, Ilona (advisor)
This thesis describes basics of methods and algorithms used in computer vision and application of them at a simple practical problem – line-tracking for delivery robot. The first part of this thesis contains basic theoretical knowledge of computer vision, which is important for understanding the problem. It is an introduction to problems of computer vision. The second part of thesis describes solving of particular steps, which are image preprocessing, segmentation, trajectory detection and algorithms for direction control. It contains outcomes of particular steps and selection of methods acceptable for solving the problem. There are presented experiences with tests of algorithms on the UTAR platform in context of this work. The last part of thesis is evaluating results taken during work.
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Point cloud clustering
Mrkvička, Daniel ; Štarha, Pavel (referee) ; Procházková, Jana (advisor)
This bachelor's thesis deals with the point cloud clustering. It focuses on surface detection in three-dimensional space. It describes in particular the methods that are used for plane detection. It also describes the concrete implementation of one of these method, the RANSAC, and examines its practical application for roof detection.
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Segmentation in the color fundus imges
Malínský, Miloš ; Jiřík, Radovan (referee) ; Kolář, Radim (advisor)
Optic nerve head and macula are important structures in fundus images. Detection and measurement plays crucial role in several diagnosis methods of optic disease. This work is focused on the detection of the central point of macula and optic nerve head, where the inner border is detected too. There are many methods for extracting this structure in retinal images. Due to the unique properties of each acquisition technique, a single generally acknowledged detection algorithm does not exist. The whole detection process is described from preprocessing through segmentation towards postprocessing. Presented methods are based on the combination of correlation techniques, Hough transform, active contours and morphological operations. The detected contours of the optic nerve head are evaluated and quantitatively compared with the contour drawn by experienced ophthalmologist. The master thesis contains quantity of images that help to describe detection methods.
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Point and Line Parameterizations Using Parallel Coordinates for Hough Transform
Juránková, Markéta ; Kälviäinen, Heikki (referee) ; Kittler, Josef (referee) ; Herout, Adam (advisor)
Tato dizertační práce se zaměřuje na použití paralelních souřadnic pro parametrizaci čar a bodů. Paralelní souřadný systém má souřadnicové osy vzájemně rovnoběžné. Bod ve dvourozměrném prostoru je v paralelních souřadnicích zobrazen jako přímka a přímka jako bod. Toho je možné využít pro Houghovu transformaci - metodu, při které body zájmu hlasují v prostoru parametrů pro danou hypotézu. Parametrizace pomocí paralelních souřadnic vyžaduje pouze rasterizaci úseček, a proto je velmi rychlá a přesná. V práci je tato parameterizace demonstrována na detekci maticových kódů a úběžníků.
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Biometry based on iris images
Tobiášová, Nela ; Drahanský, Martin (referee) ; Kolář, Radim (advisor)
The biometric techniques are well known and widespread nowadays. In this context biometry means automated person recognition using anatomic features. This work uses the iris as the anatomic feature. Iris recognition is taken as the most promising technique of all because of its non-invasiveness and low error rate. The inventor of iris recognition is John G. Daugman. His work underlies almost all current public works of this technology. This final thesis is concerned with biometry based on iris images. The principles of biometric methods based on iris images are described in the first part. The first practical part of this work is aimed at the proposal and realization of two methods which localize the iris inner boundary. The third part presents the proposal and realization of iris image processing in order to classifying persons. The last chapter is focus on evaluation of experimental results and there are also compared our results with several well-known methods.
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Image-Based Licence Plate Recognition
Vacek, Michal ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
In first part thesis contains known methods of license plate detection. Preprocessing-based methods, AdaBoost-based methods and extremal region detection methods are described.Finally, there is a described and implemented own access using local detectors to creating visual vocabulary, which is used to plate recognition. All measurements are summarized on the end.
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