|
|
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.
|
|
|
Mobil Application Support for Nine Men's Morris Playing
Kolínek, Daniel ; Zbořil, František (referee) ; Zbořil, František (advisor)
The aim of this work is to create an application for mobile device solving the task of determination the best move in game Nine men's morris from a camera snapshot taken on smart device. The task is divided into the problem of position detection and determination of the best move. Position recognition is solved by using edge detection, finding circles using Hough transform and subsequent color detection in found circles. Finding the best move is solved by own position evaluation and state space search using the Alpha-Beta algorithm. Using the OpenCV library and the Android Studio development environment, a sample application executable under Android version 5 and higher was created. The sample application solves both tasks.
|
|
|
Bifurcation Localization in Retina Images
Pres, Martin ; Drahanský, Martin (referee) ; Semerád, Lukáš (advisor)
From biometrical point of view, main features of retina are fovea, optic nerve and blood vessel tree. Blood vessel tree is unique for each person and this biological feature is used in biometric systems for person-recognition by retinal images. This document describes methods for optic disc and fovea localization, method for vessel tree segmentation, which is based on well-known \emph{Matched filters} method and also describes method for localization of blood vessel bifurcations. Main goal of this thesis is creation of program which can automatically preprocess input image, segment blood vessels and localize vessel bifircations. The program is implemented in Java with OpenCV library.
|
|
|
Mobil Application Support for Nine Men's Morris Playing
Kolínek, Daniel ; Zbořil, František (referee) ; Zbořil, František (advisor)
The aim of this work is to create an application for mobile device solving the task of determination the best move in game Nine men's morris from a camera snapshot taken on smart device. The task is divided into the problem of position detection and determination of the best move. Position recognition is solved by using edge detection, finding circles using Hough transform and subsequent color detection in found circles. Finding the best move is solved by own position evaluation and state space search using the Alpha-Beta algorithm. Using the OpenCV library and the Android Studio development environment, a sample application executable under Android version 5 and higher was created. The sample application solves both tasks.
|
|
|
Bifurcation Localization in Retina Images
Pres, Martin ; Drahanský, Martin (referee) ; Semerád, Lukáš (advisor)
From biometrical point of view, main features of retina are fovea, optic nerve and blood vessel tree. Blood vessel tree is unique for each person and this biological feature is used in biometric systems for person-recognition by retinal images. This document describes methods for optic disc and fovea localization, method for vessel tree segmentation, which is based on well-known \emph{Matched filters} method and also describes method for localization of blood vessel bifurcations. Main goal of this thesis is creation of program which can automatically preprocess input image, segment blood vessels and localize vessel bifircations. The program is implemented in Java with OpenCV library.
|
|
|
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.
|
guest ::
