National Repository of Grey Literature 29 records found  previous11 - 20next  jump to record: Search took 0.01 seconds. 
Traffic lanes and interruptions detection
Dojava, Marian ; Červinka, Luděk (referee) ; Horák, Karel (advisor)
This master´s thesis deals with depiction aplication of camera like sensitive element for assisting system of car. It was proposed, how find a road, a lane and a obstacle on roadways. Only one camera was aplication for it. Solution is realized by methods, that are based on color and gradient of image. It applies simple methods and methods with mathematical model. Result is sum of method and its test and comparing. Realization of my program is present at resume of this thesis.
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.
Tracking of Military Objects in a Videosignal
Hamada, Ondřej ; Váňa, Jan (referee) ; Orság, Filip (advisor)
First part of this thesis briefly describes the main problems of object tracking in video and methods to deal with them. Main attention is paid towards usage of these methods for target tracking in videos taken by both normal and thermal camera. It propose solution to this problem based on the kernel-based method which uses mean-shift algorhitm and on the template matching. Both tracking methods results are supervised and corrected by Kalman filter. Proposed solution is implemented using C++ with OpenCV library.
Analysis of cytology images
Pavlík, Jan ; Blaha, Milan (referee) ; Kolář, Radim (advisor)
This master’s thesis is focused on automating the process of differential leukocyte count in peripherial blood using image processing. It deals with the design of the processing of digital images - from scanning and image preprocessing, segmentation nucleus and cytoplasm, feature selection and classifier, including testing on a set of images that were scanned in the context of this work. This work introduces used segmentation methods and classification procedures which separate nucleus and the cytoplasm of leukocytes. A statistical analysis is performed on the basis of these structures. Following adequate statistical parameters, a set of features has been chosen. This data then go through a classification process realized by three artificial neural networks. Overall were classified 5 types of leukocytes: neutropfiles, lymphocytes, monocytes, eosinophiles and basophiles. The sensitivity and specificity of the classification made for 4 out of 5 leukocyte types (neutropfiles, lymphocytes, monocytes, eosinophiles) is higher than 90 %. Sensitivity of classiffication basophiles was evaluated at 75 % and specificity at 67 %. The total ability of classification has been tested on 111 leukocytes and was approximately 91% successful. All algorithms were created in the MATLAB program.
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.
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.
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.
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.
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.
Tracking of Military Objects in a Videosignal
Hamada, Ondřej ; Váňa, Jan (referee) ; Orság, Filip (advisor)
First part of this thesis briefly describes the main problems of object tracking in video and methods to deal with them. Main attention is paid towards usage of these methods for target tracking in videos taken by both normal and thermal camera. It propose solution to this problem based on the kernel-based method which uses mean-shift algorhitm and on the template matching. Both tracking methods results are supervised and corrected by Kalman filter. Proposed solution is implemented using C++ with OpenCV library.

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