Thesis Details
Analýza rozložení textu v historických dokumentech
The goal of this thesis is to design and implement algorithm for text layout analysis in historical documents. Neural network was used to solve this problem, specifically architecture Faster-RCNN. Dataset of 6 135 images with historical newspaper was used for training and testing. For purpose of the thesis four models of neural networks were trained: model for detection of words, headings, text regions and model for words detection based on position in line. Outputs from these models were processed in order to determine text layout in input image. A modified F-score metric was used for the evaluation. Based on this metric, the algorithm reached an accuracy almost 80 %.
document layout analysis, neural networks, Faster-RCNN, Python, image processing
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Beran Vítězslav, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Lengál Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Zemčík Pavel, prof. Dr. Ing. (DCGM FIT BUT), člen
@mastersthesis{FITMT23653,
author = "Bianca Palackov\'{a}",
type = "Master's thesis",
title = "Anal\'{y}za rozlo\v{z}en\'{i} textu v historick\'{y}ch dokumentech",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/23653/"
}