Fast Anisotropic Filtering and Performance Evaluation Tool for Optical Flow in Biomedical Image Analysis
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F11%3A00052079" target="_blank" >RIV/00216224:14330/11:00052079 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Fast Anisotropic Filtering and Performance Evaluation Tool for Optical Flow in Biomedical Image Analysis
Popis výsledku v původním jazyce
The thesis is focused on the analysis of time-lapse images acquired using a fluorescence light microscope. In particular, for the purpose of automated evaluation of motion of stained cell structures, e.g., proteins or cell nuclei, perceived over a time period, we aim towards an object tracking based on an optical flow field. An optical flow method estimates a flow field in which a vector is assigned to every pixel in an image. The vector represents the difference in position of the same pixel content between two images. To track the given position it is then enough to simply follow flow vectors provided good flow estimates are available. The thesis reviews the process from acquiring image data to methods for computing optical flow. The description starts with the limits of the imaging technology and characterization of the obtained image data. The survey part reviews and discusses methods that allow for conducting object tracking.
Název v anglickém jazyce
Fast Anisotropic Filtering and Performance Evaluation Tool for Optical Flow in Biomedical Image Analysis
Popis výsledku anglicky
The thesis is focused on the analysis of time-lapse images acquired using a fluorescence light microscope. In particular, for the purpose of automated evaluation of motion of stained cell structures, e.g., proteins or cell nuclei, perceived over a time period, we aim towards an object tracking based on an optical flow field. An optical flow method estimates a flow field in which a vector is assigned to every pixel in an image. The vector represents the difference in position of the same pixel content between two images. To track the given position it is then enough to simply follow flow vectors provided good flow estimates are available. The thesis reviews the process from acquiring image data to methods for computing optical flow. The description starts with the limits of the imaging technology and characterization of the obtained image data. The survey part reviews and discusses methods that allow for conducting object tracking.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2011
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů