Thesis Details

Detekce graffiti tagů v obraze

Bachelor's Thesis Student: Fischer Martin Academic Year: 2018/2019 Supervisor: Špaňhel Jakub, Ing.
English title
Detection of Graffiti Tags in Image
Language
Czech
Abstract

The aim of this work is to compare different approaches of computer vision with the intention of automatic detection of graffiti tags in the image. The solution was based on models based on neural networks. Both the proven detection models and the experimental models were tested here. The most accurate one (Faster R-CNN) achieved an accuracy of 83% mAP, indicating the suitability of these models to the tag detection problem.

Keywords

object detection, graffiti tags, convolutional neural network, Faster R-CNN, R-FCN, Mask R-CNN, EAST detector, CCNN, Counting CNN

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
11 June 2019
Reviewer
Kodym Oldřich, Ing., Ph.D.
Committee
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Citation
FISCHER, Martin. Detekce graffiti tagů v obraze. Brno, 2019. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-11. Supervised by Špaňhel Jakub. Available from: https://www.fit.vut.cz/study/thesis/20821/
BibTeX 
@bachelorsthesis{FITBT20821,
    author = "Martin Fischer",
    type = "Bachelor's thesis",
    title = "Detekce graffiti tag\r{u} v obraze",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/20821/"
}

Theses

Back to top