Computer Aided Recognition and Classification of Coats of Arms

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)


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.


Image segmentation Neural networks Heraldry 



This work was supported by the BUT project FIT-S-17-4014 and the IT4IXS: IT4Innovations Excellence in Science project (LQ1602).


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.FIT, IT4Innovations Centre of ExcellenceBrno University of TechnologyBrnoCzech Republic

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