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Computer Science > Computer Vision and Pattern Recognition

arXiv:2108.11667 (cs)
[Submitted on 26 Aug 2021]

Title:StackMix and Blot Augmentations for Handwritten Text Recognition

Authors:Alex Shonenkov, Denis Karachev, Maxim Novopoltsev, Mark Potanin, Denis Dimitrov
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Abstract:This paper proposes a handwritten text recognition(HTR) system that outperforms current state-of-the-artmethods. The comparison was carried out on three of themost frequently used in HTR task datasets, namely Ben-tham, IAM, and Saint Gall. In addition, the results on tworecently presented datasets, Peter the Greats manuscriptsand HKR Dataset, are this http URL paper describes the architecture of the neural net-work and two ways of increasing the volume of train-ing data: augmentation that simulates strikethrough text(HandWritten Blots) and a new text generation method(StackMix), which proved to be very effective in HTR this http URL can also be applied to the standalone task of gen-erating handwritten text based on printed text.
Comments: 17 pages, 9 figures
Subjects: Computer Vision and Pattern Recognition (cs.CV)
MSC classes: 68-04
ACM classes: I.7.5; I.4.6
Cite as: arXiv:2108.11667 [cs.CV]
  (or arXiv:2108.11667v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2108.11667

Submission history

From: Denis Dimitrov [view email]
[v1] Thu, 26 Aug 2021 09:28:22 UTC (5,630 KB)
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