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Conference Paper A screen of slide detection method using deep learning-based segmentation and Hough transform
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Authors
Junyoung Hong, Sunguk Jung, Yongwoo Lee, Hyeonbeom Heo, Hyeri Yang, Hayeon Kim, Kyungjae Lee
Issue Date
2022-07
Citation
International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2022, pp.272-274
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ITC-CSCC55581.2022.9894959
Abstract
Recently, COVID-19 has accelerated the non-contact culture. Many presentations, such as workshops and conferences, are conducted in an online and offline hybrid mode in a conference room. In presentations, a screen of the slide is particularly important. Therefore, we propose an algorithm that detects the screen in an image. Firstly, a screen region is extracted using a deep learning-based instance segmentation method. However, this extracted region has a noisy boundary. We designed an image processing algorithm composed of 7 main steps to solve this noise and detect the screen. To validate the proposed method, a real dataset was qualitatively evaluated, and the result images show that only meaningful screen regions in the test image can be extracted.
KSP Keywords
Detection Method, Hough transform, Image processing(IP), Image processing algorithm, Learning-based, Non-contact, Online and Offline, deep learning(DL), hybrid mode, segmentation method