학술논문

A screen of slide detection method using deep learning-based segmentation and Hough transform
Document Type
Conference
Source
2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) Circuits/Systems, Computers and Communications (ITC-CSCC), 2022 37th International Technical Conference on. :272-274 Jul, 2022
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Computers
COVID-19
Image segmentation
Conferences
Transforms
Companies
Feature extraction
Segmentation
deep learning
image processing
Hough transform
K-means clustering
Language
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.