Publication Details
Computer Aided Recognition and Classification of Coats of Arms
Convolutional Neural Networks, Image Processing, Segmentation, Heraldy
This paper describes the design and development of a system for detection and recognition of coat of arms and its heraldic parts (components). It introduces the methods by which individual features can be implemented. Most of the heraldic parts are segmented using a convolution neural networks and the rest of them are segmented using active contour model. The Histogram of the gradient method was chosen for coats of arms detection in an image. For training and functionality verification we used our own data that was created as a part of our research. The resulting system can serve as an auxiliary tool used in heraldry and other sciences related to history.
@INPROCEEDINGS{FITPUB11534,
author = "Franti\v{s}ek V\'{i}de\v{n}sk\'{y} and Franti\v{s}ek Zbo\v{r}il",
title = "Computer Aided Recognition and Classification of Coats of Arms",
pages = "63--73",
booktitle = "Proceedings ISDA 2017",
series = "Advances in Intelligent Systems and Computing, vol 736",
journal = "Advances in Intelligent Systems and Computing",
volume = 2018,
number = 3,
year = 2018,
location = "Los Alamitos, US",
publisher = "Springer International Publishing",
ISBN = "978-3-319-76347-7",
ISSN = "2194-5357",
doi = "10.1007/978-3-319-76348-4\_7",
language = "english",
url = "https://www.fit.vut.cz/research/publication/11534"
}