Conference paper

VÍDEŇSKÝ František and ZBOŘIL František. Computer Aided Recognition and Classification of Coats of Arms. In: Proceedings ISDA 2017. Los Alamitos: Springer International Publishing, 2018, pp. 63-73. ISBN 978-3-319-76347-7. ISSN 2194-5357.
Publication language:english
Original title:Computer Aided Recognition and Classification of Coats of Arms
Title (cs):Počítačová podpora pro rozpoznávání a klasifikaci rodových erbů
Proceedings:Proceedings ISDA 2017
Conference:17th International Conference on Intelligent Systems Design and Applications
Series:Advances in Intelligent Systems and Computing, vol 736
Place:Los Alamitos, US
Journal:Advances in Intelligent Systems and Computing, Vol. 2018, No. 3, CZ
Publisher:Springer International Publishing
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.
   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},
   language = {english},
   url = {}

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