National Repository of Grey Literature 29 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
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.
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.
Automatizovaná detekce makromolekulárních komplexů z kvantitativních STEM snímků a výpočet jejich molekulární hmotnosti
Záchej, Samuel ; Walek, Petr (referee) ; Hrubanová, Kamila (advisor)
This bachelor’s thesis deals with problems of processing and analysis of images from quantitative STEM microscope. The thesis describes principles of image formation and methods of image processing. An essential part is a description of properties and classification of detected macromolecular complexes. A practical part includes processing of exemplary images in MATLAB. An important part is a design and realization of the algorithm for detection objects in the image, their classification and calculation of their molecular mass. The thesis includes testing of used algorithms and analysis of the results.
Parallelization and Optimization of Image Processing Applications
Šiška, Jakub ; Seeman, Michal (referee) ; Černocký, Jan (advisor)
This Bachelor's Thesis was performed during a study stay at the École Supérieure d'Ingénieurs en Électronique et Électrotechnique Paris, France. It proposes solution for speeding up image processing algorithm and its adoption for use with real-time video stream from the infra red camera. The first part discusses characteristics and basic principles of the IR technology, followed by specifications of used camera. Ongoing text also proposes solution of problems concerning network communication with the camera. In addition, it describes camera's output stream format characteristics and solution for output visualisation. Substantial part of this work covers issues concerning parallelization and optimization of video stream and image file data processing. Problem of the parallelisation for this case is explained together with implemented parallelization method. Entire theoretical part is supported with the real results, benchmarks, which are presented in the last chapter.
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.
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.
Topology Recognition from Crossroad Plan
Huták, Petr ; Bartík, Vladimír (referee) ; Kreslíková, Jitka (advisor)
This master‘s thesis describes research, design and development of system for topology recognition from crossroad plan. It explains the methods used for image processing, image segmentation, object recognition. It describes approaches in processing of maps represented by raster images and target software, in which the final product of practical part of project will be integrated. Thesis is focused mainly on comparison of different approaches in feature extraction from raster maps and determination their semantic meaning. Practical part of project is implemented in C# language with OpenCV library.
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.
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.
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.

National Repository of Grey Literature : 29 records found   1 - 10nextend  jump to record:
Interested in being notified about new results for this query?
Subscribe to the RSS feed.