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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
- Language
- English
- Type
- Conference Paper
- Project Code
- 22HH9200, Development of real·virtual environmental analysis based adaptive interaction technology, Jung Sung Uk
- 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, Image Processing algorithm, Learning-based, Non-contact, Online and Offline, deep learning(DL), hough transform, hybrid mode, segmentation method