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6 November 2019 Widget detection on screenshots using computer vision and machine learning algorithms
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Proceedings Volume 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019; 111761Q (2019) https://doi.org/10.1117/12.2536406
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 2019, Wilga, Poland
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kacper Radzikowski, Karol Chęciński, Mateusz Forc, Łukasz Lepak, Michał Jabłoński, Wiktor Kuśmirek, Bartłomiej Twardowski, Paweł Wawrzyński, and Robert M. Nowak "Widget detection on screenshots using computer vision and machine learning algorithms", Proc. SPIE 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 111761Q (6 November 2019); https://doi.org/10.1117/12.2536406
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