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Widget detection on screenshots using computer vision and machine learning algorithms
Author(s): Kacper Radzikowski; Karol Chęciński; Mateusz Forc; Łukasz Lepak; Michał Jabłoński; Wiktor Kuśmirek; Bartłomiej Twardowski; Paweł Wawrzyński; Robert M. Nowak
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Paper Abstract

In this paper we consider the problem of detecting and recognizing widgets in screenshots of computer programs’ graphical user interface (GUI). This problem is fundamental in business process automation. The solution we propose here is based on detecting GUI elements with Canny edge operator, and recognizing already detected GUI elements with classifiers: neural networks, random forests, XGBoost, and others.

Paper Details

Date Published: 6 November 2019
PDF: 8 pages
Proc. SPIE 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 111761Q (6 November 2019); doi: 10.1117/12.2536406
Show Author Affiliations
Kacper Radzikowski, Warsaw Univ. of Technology (Poland)
Karol Chęciński, Warsaw Univ. of Technology (Poland)
Mateusz Forc, Warsaw Univ. of Technology (Poland)
Łukasz Lepak, Warsaw Univ. of Technology (Poland)
Michał Jabłoński, MakeItRight Ltd. (Poland)
Wiktor Kuśmirek, Warsaw Univ. of Technology (Poland)
Bartłomiej Twardowski, Warsaw Univ. of Technology (Poland)
Paweł Wawrzyński, Warsaw Univ. of Technology (Poland)
Robert M. Nowak, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 11176:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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