Thesis Details

Pokročilé metody detekce hran v obraze

Master's Thesis Student: Mezírka Martin Academic Year: 2014/2015 Supervisor: Španěl Michal, Ing., Ph.D.
English title
Advanced Image Edge Detection
Language
Czech
Abstract

The goal of this work is to investigate options how to apply trainable edge detection algorithm Structured forest for fast edge detection to information extraction from historici maps and medical images. For the work, annotated dataset was created and the detektor was tested on it. Structured forest achieved better results on map data, compared with classical detectors. Success rate of finding edges of bones was similar at both approaches. Aim of the work is focused on comparing different image annotation styles, experiments with dataset, including determining parameters and evaluation of the methods.

Keywords

Edge detection, annotation tool, boundary dataset.

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology, Field of Study Computer Graphics and Multimedia
Files
Status
defended, grade C
Date
23 June 2015
Reviewer
Bařina David, Ing., Ph.D.
Committee
Zemčík Pavel, prof. Dr. Ing. (DCGM FIT BUT), předseda
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
Strnadel Josef, Ing., Ph.D. (DCSY FIT BUT), člen
Šlapal Josef, prof. RNDr., CSc. (DADM FME BUT), člen
Španěl Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Citation
MEZÍRKA, Martin. Pokročilé metody detekce hran v obraze. Brno, 2015. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2015-06-23. Supervised by Španěl Michal. Available from: https://www.fit.vut.cz/study/thesis/11360/
BibTeX 
@mastersthesis{FITMT11360,
    author = "Martin Mez\'{i}rka",
    type = "Master's thesis",
    title = "Pokro\v{c}il\'{e} metody detekce hran v obraze",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2015,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/11360/"
}

Theses

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