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Methods for biomedical image signal segmentation
Krumpholc, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work deals with methods of segmentation of biomedical image signals. It describes, sums up and compares representative methods of digital image processing. Segmentation based on parametric representation is one of the mentioned methods. So as the basic parameter can be chosen for example luminance and the final binary image is obtained by thresholding. Next described method is segmentation based on edge representation. This method can be divided into edge detection by the help of edge detectors and of Hough transformation. Edge detectors work with the first and second derivation. The following method is region-based segmentation, which can be used for a image with noise. This category can be divided into three parts. The first one is segmentation via splitting and merging regions, when the image is split and the created regions are tested on a defined condition. If the condition is satisfied, the region merges and doesn’t continue splitting. The second one is region growing segmentation, when adjacent pixels with a similar intensity of luminance are grouped together and create a segmentated region. Third one is watershed segmentation algorithm based on the idea of water diffusion on uneven surface. The last group of methods is segmentation via flexible and active contours. Here is described an active shape model proceeding from a possibility to deform models so that they match with sample shapes. Next I also describe method Snakes, where occurs gradual contour shaping up to the edge of the object in the image. For the final editing is used mathematical morphology of segmentated images. I aimed to meet methods of image signals segmentation, to cover the chosen methods as a script in programming language Matlab and to check their properties on images.
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Advanced methods for cardiac cells contour detection
Spíchalová, Barbora ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This thesis focuses on advanced methods of detecting contours of the cardiac cells and measuring their contraction. The theoretical section describes the types of confocal microscopes, which are used for capturing biological samples. The following chapter is devoted to the methods of cardiac cells segmentation, where we are introduced to the generally applied approaches. The most widely spread methods of segmentation are active contours and mathematical morphology, which are the crucial topics of this thesis. Thanks to the those methods we are able in the visual data to accurately detect required elements and measure their surface chnage in time. Acquired theoretical knowledge leads us to the practical realization of the methods in MATLAB.
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Line Detection with Different Size
Váňa, Lukáš ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
This Bachelor Theses deals with question of the location of the set thicknesses of lines in the picture. It summarizes theoretical basis and procedures for the elaboration of the incoming signal and the Theory of the edge detection. It mentioned current known methods for lines detection in the picture. By the assist of these methods, extended of another known procedures, this theses suggested algorithm, able to detect line of the set thickness in the picture. It describes also suggestion of the realization of the application, which demonstrates utility of the created algorithm. The application is the programming part of this Theses.
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Hand Gesture Recognition
Adámek, Jakub ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis is focused on human hand gesture recognition. The main part of the work deals with image segmentation of videosequences for further gesture recognition. For the image segmentation, techniques such as face detection followed by skin detection in combination with background subtraction method are used. In order to eliminate noise, methods of mathematic morphology are applied. The work focuses only on dynamic hand gesture recognition. The proposed gesture recognition system is inspirited by hidden Markov model method. The last chapter of the thesis discusses the accuracy of the gesture recognition.
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Morphological Operations in Image Processing
Kolouchová, Michaela ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
Mathematical morphology stems from set theory and it makes use of properties of point sets. The first point set is an origin image and the second one (usually smaller) is a structuring element. Morphological image transformations are image to image transformations based on a few elementary set operators. Fundamental morphologic operations are dilation, erosion and hit or miss. Next operations described in this work are opening and closing. Originally morphological operators were used for binary images only, later they were generalized for grey tone and color ones. This work describes the basic morphological image processing methods including their practical usage in image filtering and segmentation.
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Blood vessel segmentation in fundus images using mathematical morphology
Stonawski, Stanislav ; Jan, Jiří (referee) ; Odstrčilík, Jan (advisor)
Segmentation of retinal blood vessel is an important step in the fundus image analysis. The resulting image can be used to diagnose ophthalmic or cardiovascular diseases. The aim of this thesis is to search for possibilities of high resolution eye fundus image processing while using mathematical morphology methods. This should lead to the creation of an algorithm capable of blood vessel segmentation. The thesis provides information on fundus camera, image, blood vessel properties and mathematical morphology filtering methods. The created algorithms and the proposed method based on them are presented, including their performance analysis based on the HRF database processing.
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Measurement of thickness of skin and subcutaneous tissue in B-mode ultrasound image
Moldříková, Zuzana ; Štohanzlová, Petra (referee) ; Šrámek, Jaromír (advisor)
In the first part this bachelor thesis deals with theoretical analysis of terms, which are needed for understanding and algorithm proposition for skin thickness and subcutaneous tissue direct measurement. Second part of this thesis deals with implementation of algorithm. In six chapters there are described terms like skin and subcutaneous tissue, adiposity, Body Composition Analysis, ultrasound, B-mode and basics of image processing, which are going to be needed for processing of ultrasound image and algorithm creation. Chapter seven includes description of algorithm implementation and description of its structure. There is also analyzed clinical verification of functionality on phantom and some volunteers. The chapter is concluded with evaluation and discussion of gained results.
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Retinal images in biometry
Bujnošková, Eva ; Drahanský, Martin (referee) ; Kolář, Radim (advisor)
Retinal recognition is very efficient and almost non-fallible tool for persons' identification, thanks its advantages it can be used in cases when high security is needed. Process of the identification comes from successful vessel extraction and the transfer to binary image. After that this is used to look for the vessel bifurcations with help of skeletonization which is one of the operations of mathematical morphology. The parameter of the detection of bifurcations isn't enough therefore there are other information completed - thickness and the direction of vessel in the surroundings of known crossing. The best correlation between the parameters and the images in database is searched, than alignment is made, and with the certain probability the closest image is chosen to be proclaimed as the match. The solution uses also the second method to image processing - the method using image translation and evaluation of minimal distances between found bifurcations.
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Image based road surface segmentation with lane detection
Turoň, Rudolf ; Honec, Peter (referee) ; Zemčík, Tomáš (advisor)
This bachelor thesis deals with road semantic segmentation with lane lines detection. The aim of the thesis is to conduct a survey of methods used for general segmentation and lane lines detection, collect a representative dataset for testing, design a data processing system including implementation for semantic segmentation and detection of lanes in image, video and live camera input. In preprocessing phase images are filtered using morphological transformations. The segmentation is performed using the watershed method with labels, and an adaptive algorithm is designed to find the labels. The lanes are searched for in the thresholded projectively transformed image using the sliding window technique. As a result, a segmentation accuracy of 88.3% is achieved based on the IoU metric. The thesis concludes with a discussion of the obtained results and summarizes the possibilities for further improvements of the system.
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Game with Hand Gesture Control
Kartous, Petr ; Zemčík, Pavel (referee) ; Hradiš, Michal (advisor)
This work is focused on controlling the game by using hand gestures. The main part of the work is image segmentation and detection of the hand in picture. For the segmentation of the image are used techniques of skin detection and the background subtraction with adaptive model of the background. Also the methods of mathematical morphology to eliminate the noise from the image and the appropriate methods for transferring images of gestures to characteristic gestures in numerical form are mentioned. In the context of the work was a simple car race game created which is controlled by hand gestures. At the end there was a testing carried out to identify the advantages and disadvantages of used methods of image segmentation and to detect the used hand gestures. There were also several sets of gestures tested by which the game is controlled. The two sets which came out of the test most successfully are applicable depending on the quality of the hand gesture recognition.
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