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Application for Recognition of Human Eye Retina
Drozd, Radek ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The blood vessels layout in a human eye retina is unique for every person in the world, so it is one of important biometric characteristics. Processing of colour retina image may be a part of an intended biometric system. There is an algorithm for automatic blood vessels detection, optic disc and macula localisation, finding of bifurcation points and saving those as a biometric template presented in this bachelor's thesis. C++ programming language and OpenCV library were used for implementation. The application was tested on a set of colour retina images, taken by fundus camera. The final application is supposed to run on a digital signal processor, developed by Texas Instruments. The thesis gives the introduction into biometrics, signal processing and human eye anatomy.
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Vein-Artery Segmentation of Blood Vessels in Retinal Images
Sedlář, Radek ; Kanich, Ondřej (referee) ; Kavetskyi, Andrii (advisor)
This work focuses on an introduction to the issue of segmentation of veins and arteries from retinal images. The work contains a comparison of the most used methods with their pros and cons. Furthermore, a proprietary method for segmentation and division into veins and arteries is proposed. The work also contains a detailed description of the implementation of the proposed method and a summary of their results.
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Segmentation in microscopic images
Vlk, Jaroslav ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Work studying the properties of microscopic images and then the following applies in the segmentation of the image. Work is trying to use a simpler methods image processing mainly. At the same time, deals with methods for preprocessing image. In the choice of methods and the use of emphasis on speed and simplicity of calculation.
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Analysis of Colour Retinal Images Aimed at Segmentation of Vessel Structures
Odstrčilík, Jan ; Jiřík, Radovan (referee) ; Jan, Jiří (advisor)
Segmentation of vessel structure is an important phase in analysis of retinal images. The resulting vessel system description may be important for diagnostic of many eye and cardiovascular diseases. A method for automatic segmentation of the vessel structure in colour retinal images is presented in the thesis. The method utilises 2D matched filtering to detect presence of short linear vessel sections of a particular thickness and orientation. The approach correlates the local image areas with a 2D masks based on a typical brightness profile perpendicular to vessels of a particular width. Three different approximated profiles are used and corresponding matched filters are designed for: thin, medium and thick vessels. The evaluation of typical vessel profiles and filter design are described in chapter 3 and chapter 4. The parametric images obtained by convolution of the image with the masks are then thresholded in order to obtain binary representation of vessel structure. The three binary representations are consequently combined to provide the best available rough vessel map, which is finalised by complementing the obviously missing vessel sections and cleaning the disconnected fractional artefacts. The thresholding algorithm and final steps of processing are mentioned in chapter 5 and chapter 6. The method has been implemented by computer and the program for automatic vessel segmentation has been developed using database of real retinal images. The efficiency of the method has been finally evaluated on images from the standard database DRIVE.
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Optimization techniques in image applications
Ondráček, Pavel ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.
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Blood vessel segmentation in high resolution retinal images
Svobodová, Sabina ; Odstrčilík, Jan (referee) ; Valterová, Eva (advisor)
This thesis focuses on implementation of an algorithm for retinal vessel segmentation in high resolution retinal images.A neural network with two hidden layers was used as the method. A total of 7 features were obtained from matched filtering based on vessel thickness, texture analysis and individual pixels brightness. Within the thesis, the whole database was manually annotated for the implementation of the algorithm and the results. The achieved mean sensitivity reached 80%, specificity 70% and Dice coefficient is 59%.
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Vein-Artery Segmentation of Blood Vessels in Retinal Images
Sedlář, Radek ; Kanich, Ondřej (referee) ; Kavetskyi, Andrii (advisor)
This work focuses on an introduction to the issue of segmentation of veins and arteries from retinal images. The work contains a comparison of the most used methods with their pros and cons. Furthermore, a proprietary method for segmentation and division into veins and arteries is proposed. The work also contains a detailed description of the implementation of the proposed method and a summary of their results.
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Optimization techniques in image applications
Ondráček, Pavel ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.
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Blood vessel segmentation in high resolution retinal images
Svobodová, Sabina ; Odstrčilík, Jan (referee) ; Valterová, Eva (advisor)
This thesis focuses on implementation of an algorithm for retinal vessel segmentation in high resolution retinal images.A neural network with two hidden layers was used as the method. A total of 7 features were obtained from matched filtering based on vessel thickness, texture analysis and individual pixels brightness. Within the thesis, the whole database was manually annotated for the implementation of the algorithm and the results. The achieved mean sensitivity reached 80%, specificity 70% and Dice coefficient is 59%.
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|
|
Application for Recognition of Human Eye Retina
Drozd, Radek ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The blood vessels layout in a human eye retina is unique for every person in the world, so it is one of important biometric characteristics. Processing of colour retina image may be a part of an intended biometric system. There is an algorithm for automatic blood vessels detection, optic disc and macula localisation, finding of bifurcation points and saving those as a biometric template presented in this bachelor's thesis. C++ programming language and OpenCV library were used for implementation. The application was tested on a set of colour retina images, taken by fundus camera. The final application is supposed to run on a digital signal processor, developed by Texas Instruments. The thesis gives the introduction into biometrics, signal processing and human eye anatomy.
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