Single-image background removal with entropy filtering

Chang Chieh Cheng*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Background removal is often used for segmentation of the main subject from a photograph. This paper proposes a new method of background removal for a single image. The proposed method uses Shannon entropy to quantify the texture complexity of background and foreground areas. A normalized entropy filter is applied to compute the entropy of each pixel. The pixels can be classified effectively if the entropy distributions of the background and foreground can be distinguished. To optimize performance, the proposed method constructs an image pyramid such that most background pixels can be labeled in a low-resolution image; thus, the computational cost of entropy calculation can be reduced in the image with the original resolution. Connected component labeling is also adopted for denoising to retain the main subject area completely.

原文English
主出版物標題VISAPP
編輯Giovanni Maria Farinella, Petia Radeva, Jose Braz, Kadi Bouatouch
發行者SciTePress
頁面431-438
頁數8
ISBN(電子)9789897584886
出版狀態Published - 2021
事件16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2021 - Virtual, Online
持續時間: 8 二月 202110 二月 2021

出版系列

名字VISIGRAPP 2021 - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
4

Conference

Conference16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2021
城市Virtual, Online
期間8/02/2110/02/21

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