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Preprocessing of retinal images aimed at support diagnosis of glaucoma
Holásková, Anna ; Walek, Petr (referee) ; Odstrčilík, Jan (advisor)
Preprocessing of retinal images can serve as a first phase of the further image analysis or the first step preceding diagnosing of various eye diseases. The preprocessing thus represents methods of image adjustments that can improve visual characteristics of fundus images. These methods mainly include the removal of noise generated during data acquisition, contrast and brightness transformations, edge detection and thresholding. This work handles with the basic methods of image preprocessing and specific methods of preprocessing of retinal images. The preprocessing includes global illumination correction, high-pass and homomorphic filtering and adaptive enhancement of the images. Manual methods for fundus image preprocessing that are usually based on the doctor's experience can be used as well. Hence, a procedure for enhancement of retinal images using Adobe Photoshop is mentioned in this work too. Three methods for preprocessing of fundus images were selected and implemented in MATLAB programming software. These methods include homomorphic filtering, CLAHE (Contrast Limited Adaptive Histogram Equalization) and adaptive enhancement. Experimental program functions were created and tested on the available image data. Results of the selected methods are mentioned in the conclusion section. Instructions for use of implemented functions are in appendix.
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Object Recognition by Neural Networks
Marák, Jaroslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is focused on neural networks and their classification capability in object recognition tasks. For recognition is there used neural networks with feedforward architecture which is learned by Back Propagation algorithm. We discusses about problems which appear while a choosing topology of network or using various lerning-significant parametters while a learning process. Achieved results are presented in experiments with estimation.
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Image processing within determination of topographic surface parameters
Boháč, Martin ; Ohlídal, Miloslav (referee) ; Šťastný, Jiří (advisor)
This work deal with determination topohraphic parameters of a randomly rough surface by the help of method of shearing interferometry. It is a optical method for determination surface roughness. The basic idea is based of on deformation interference strips which are made by interference of the same mutually translated monochrome luminous wavefronts. The wavefront is created after transit or reflection monochrome lights from the surface of a studied sample. The wavefronts creates picture with deformed interference strips , which carries information about character of the surface. This information can be profited by algorithms of image processing from the picture . The thesis was developed in research project MSM 0021630529 Intelligent Systems in Automation.
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Similarity Measure of Points of Interest in Image
Křehlík, Jan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This document deals with experimental verifying to use machine learning algorithms AdaBoost or WaldBoost to make classifier, that is able to find point in the second picture that matches original point in the first picture. This work also depicts finding points of interest in image as a first step of finding correspondence. Next there are described some descriptors of points of interest. Corresponding points could be useful for 3D modeling of shooted scene.
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Mobile System for Text Recognition on Android
Tomešek, Jan ; Kolář, Martin (referee) ; Zemčík, Pavel (advisor)
This thesis deals with creation of a mobile library for preprocessing of images with text which represents a part of a system for text recognition. The library is realized with emphasis on generality of use, efficiency and portability. The library providing a set of algorithms primarily for image quality assessment and text detection was created in this thesis. These algorithms enable a substantial decrease in volume of transmitted data and speed up and refinement of the recognition process. An example application for the Android platform able to analyze composition of foods stated on their wrappings was created as well. Overall, the library (system) simplifies development of mobile applications with focus on text extraction and analysis. The mobile application then provides a comfortable way of food harmfulness verification. The thesis offers a reader an overview of current solutions and tools available in this field, it provides a breakdown of important image preprocessing algorithms and guides him through the construction of the library and the application for mobile devices.
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Evaluation of Object Detection in Image
Černošek, Bedřich ; Behúň, Kamil (referee) ; Zemčík, Pavel (advisor)
The main goal of this bachelor's thesis was to propose the evaluation method of object detection. Result of this work was to create a program which performs the evaluation of object detection on suitable data sample and intuitively displays result to user. The task was to propose suitable experiments and dataset for proving correctness of evaluation. Part of this work was to find optimal parameters for face detection and optimal photo preprocessing before the face detection.
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Digital image analysis of mitotic chromosomes
Jaroš, Luboš ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
The development in modern medicine has allowed to study human genome and detect predispositions to several diseases. One of very promising techniques is the analysis of human karyotype, i.e., the number and appearance of chromosomes in the cell nucleus. The most important step in the karyotype analysis is the chromosome detection and categorization. In this work, a new algorithm for detection of chromosomes from an image of microscopic DNA sample and their categorization into seven groups was developed. The algorithm was implemented in Matlab. The accuracy of segmentation and classification was tested on a set of images from two databases with 117 and 38 images, respectively. The sensitivity of the developed segmentation reached 88% while the value of positive predictivity of segmentation reached 92%. The success rate of chromosome pairing achieves 77%.
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Widget Recognition for Visual GUI Testing
Kisela, Sebastián ; Peringer, Petr (referee) ; Smrčka, Aleš (advisor)
The bachelor thesis analyzes current methods and tools used for user interfaces testing. The thesis sets specification requirements and design of the implemented tool. Implementation and limitations of the implemented tool, which is based on visual object recognition, are explained in a detailed way. Verification process of the tool is described at the end.
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Object identification
Fábry, Tomáš ; Gogol, František (referee) ; Richter, Miloslav (advisor)
Work describes creation and functionality of created program for object recognition. Program issue from snapshot from webcam and given sample of searched object. It recognize all objects on the snapshot and marks those similar to given sample with aberrations to it. Program is created as an aplication for windows with language C/C++. For comunication with webcam and displaying results a used functions from library OpenCV. In work is shown structure of program and arrangement of data. Next are decribed most important created functions and used OpenCV functions. With them there is explained used technqiues from object recognition field and image processing. Program enviroment and options are described.
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