|
|
Retrieval study of hands gestures recognizing methods captured with camera
Rybnikář, Petr ; Kroupa, Jiří (referee) ; Kovář, Jiří (advisor)
The aim of this bachelor thesis was to get acquainted with basis methods of of image processing, which can be used for recognizing hands gestures captured with camera. After that choose one method, describe it in detail and implement the method.In the first part of this theses few methods for image processing are described. In the second part Level set method is choosen and described in more detail, this method is later implemented in MATLAB R2019a. In the last chapter results of implementation are analyzed and evaluated.
|
|
|
3d Segmentation Of The Spinal Canal And Intervertebral Discs In Mri Data
Koban, Martin
The concern of this work is development of the method for the spinal canal and intervertebral discs (IVD) segmentation in volume MRI data. The primary aim is to achieve the highest possible level of automation and accuracy allowing for reliable quantitative evaluation of the results. The algorithm is based on the random walk model in combination with a specific active contour method formulated through level set concept. The proposed approach is tested using a database of 3D T2-weighted MR images, which also contains referential manual segmentation of IVD.
|
|
|
A Comparison of Edge-Based and Region-Based Segmentation Performed with PDEs
Sliž, Jiří
The paper discusses the level set segmentation method, which employs the solution of the partial differential equation (PDE) describing the multidimensional function whose zero slice in plane xy determines the contour of the object. One of the possible approaches to the contour evolution is using the image edges; the edges define the boundaries of the segmented objects. A major disadvantage of this procedure consists in the often unclear or noisy edges, a condition that may lead to incomplete segmentation. Such a drawback related to the curve evolution is solvable through utilizing regions with similar brightness levels; consequently, the actual segmentation cannot be affected by unclear transitions between the objects and the background. The final comparison then shows that both methods find specific application within the segmentation process.
|
|
|
Segmentation of the cord canal and intervertebral discs in MRI data
Koban, Martin ; Odstrčilík, Jan (referee) ; Jakubíček, Roman (advisor)
The concern of this thesis is development of the method for the spinal canal and intervertebral discs segmentation in volume MRI data. The primary aim is to achieve the highest possible level of automation and accuracy allowing for reliable quantitative evaluation of the results. The algorithm is based on the random walk model in combination with a specific active contour method formulated through level set concept. The proposed approach is tested using a database of three-dimensional T2-weighted MR images, which also contains referential manual segmentation of intervertebral discs.
|
|
|
Level Sets of Multivariate Density Functions and their Estimates
Kubetta, Adam ; Hlubinka, Daniel (advisor) ; Zichová, Jitka (referee)
A level set of a function is defined as the region, where the function gets over the specified level. A level set of the probability density function can be considered an alternative to the traditional confidence region because on certain conditions the level set covers the region with minimal volume over all regions with a given confidence level. The benefits of using level sets arise in situations where, for example, the given random variables are multimodal or the given random vectors have strongly correlated components. This thesis describes estimates of the level set by means of a so called plug-in method, which first estimates density from the data set and then specifies the level set from the estimated density. In addition, explicit direct methods are also studied, such as algorithms based on support vectors or dyadic decision trees. Special attention is paid to the nonparametric probability density estimates, which form an essential tool for plug-in estimates. Namely, the second chapter describes histograms, averaged shifted histograms, kernel density estimates and its generalization. A new technique transforming kernel supports is proposed to avoid the so called boundary effect in multidimensional data domains. Ultimately, all methods are implemented in Mathematica and compared on financial data sets.
|
|
|
Automatic medical image segmentation using Level Set algorithm
Yerpeissov, Serik ; Burget, Radim (referee) ; Uher, Václav (advisor)
This thesis contains two main parts, theoretical and implementation. In the theoretical part, there are described the different segmentation methods. Mainly it is about description method Level Set. The aim of practical part is creation of java module for segmentation of medical data by using Level Set Methods. The work solves example of GUI for the display of results. The results should be tested
|
|
|
Methods for biomedical image signal segmentation in Java
Románek, Jakub ; Smékal, Zdeněk (referee) ; Šmirg, Ondřej (advisor)
This thesis contains two main parts, theoretical and implementation. In the theoretical part, there are described the different segmentation methods. Mainly it is about description method Level Set. The aim of practical part was to create a java module for segmentation of biomedical images using Level Set methods. The work solves example of a simple GUI for the display of results.
|
|
| |
guest ::
