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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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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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Automatic detection of neural fibers losses
Václavek, Martin ; Jiřík, Radovan (referee) ; Kolář, Radim (advisor)
This work is focused on detection of loss in nerve fibre layer on colour pictures of retina, witch are makes by fundus camera. It describe every simple objects of retina, optic nerve head, macula lutea and vascular bed. It detect optic nerve head and his near area, witch is general for detection of breakdownds. It use several metodes of picture adjusting for picture elaboration and objects detection (segmentation, thresholding, enhancement, hough transformation ). The detection of loss in nerve fibre layer is based on comparing of statistic parameters ( average, standart deviation, skewness coefficient and kurtosis coefficient histogram, entropy ) in choosed areas with and withou destruction of nerve layers. Vascular bed have badwatsh on results, cause of this we using hand choosing of essay.
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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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3D Face Reconstruction
Poulíček, Zbyněk ; Šiler, Ondřej (referee) ; Španěl, Michal (advisor)
The top of this thesis is 3D face reconstruction by the help the projected regular grid from the 2D image. It also includes the grid detection and the description of methods that are needed to raster image processing. The application was written in C++ programming language, it uses OpenCV graphic library, and also it is designed for OS Windows XP and higher.
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Edge Detection and Representation Algorithms for Object Recognition
Beránek, Jan ; Herout, Adam (referee) ; Španěl, Michal (advisor)
Main topic of this work are edge detection and representation algorithms used in an digital image. Some of typically used algorithms and methods are shown and described. Next aim of this work is design and description of implementation of a simple OCR system based on edge detection with use of an artificial neural net for a machine printed character recognition. The system was written in C programming language and uses OpenCV graphic library and FANN library for creating a neural net. Application was created and tested under Windows XP operating system.
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Automatic Processing of Tests Corrected by Hand
Pelantová, Lucie ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this bachelor's thesis is mass processing of exams corrected by hand. The essence of proposed solution is table detection. Structure of table is first detected in sample page, then this pattern is searched in processed page. Corresponding parts of table are used to compute homography. After application of transformation matrix are data segmented and send for handwritten text recognition. The thesis contains evaluation of accuracy for individual system components and possibility of use in practice. Resulting application is supposed to effectively segment data from structured documents.
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Handwritten Character Recognition Using Artificial Neural Networks
Horký, Vladimír ; Janda, Miloš (referee) ; Plchot, Oldřich (advisor)
Neural networks with algorithm back-propagation will be presented in this work. Theoretical background of the algorithm will be explained. The problems with training neural nets will be solving there. The work discuss some techniques of image preprocessing and image extraction features, which is one of main part in classification. Some part of work discuss few experiments with neural nets with chosen image features.
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Ellipse Detection
Hříbek, Petr ; Herout, Adam (referee) ; Hradiš, Michal (advisor)
The thesis introduces methods used for an ellipse detection. Each method is theoretically described in current subsection. The description includes methods like Hough transform, Random Hough transform, RANSAC, Genetic Algorithm and improvements with optimalization. Further there are described modifications of current procedures in the thesis to reach better results. Next to the last chapter represents testing parameters of speed, quality and accuracy of implemented algorithms. There is a conclusion of testing and a result discussion at the end.
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