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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Rungpanich P. | |
| dc.contributor.author | Pattanaworapan P. | |
| dc.contributor.author | Kiatsoontorn K. | |
| dc.contributor.author | Charoenpong T. | |
| dc.contributor.other | Srinakharinwirot University | |
| dc.date.accessioned | 2023-11-15T02:08:53Z | - |
| dc.date.available | 2023-11-15T02:08:53Z | - |
| dc.date.issued | 2023 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149687667&doi=10.1109%2fICA-SYMP56348.2023.10044930&partnerID=40&md5=cbd7e0f5809567a4f6423e287ecee728 | |
| dc.identifier.uri | https://ir.swu.ac.th/jspui/handle/123456789/29522 | - |
| dc.description.abstract | Contamination in operating room lead to infection in a patient specially during surgery. A touchless technology can be used to reduce contamination in the operating room when surgeon uses an X-ray image viewer. Skin segmentation is an important processing for touchless image viewer in an operating room. In this paper, we proposed a skin color segmentation method using threshold in color space. This method consists of three steps: 1) frame extraction, 2) color space conversion, 3) skin color segmentation. To test the performance of the proposed method, 601 images are used in the experiment. Accuracy rate is 50.46%. This is satisfactory for applying implementation algorithm for hand detection in future. © 2023 IEEE. | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.subject | contamination | |
| dc.subject | hand movement | |
| dc.subject | operating room | |
| dc.subject | skin color segmentation | |
| dc.subject | surgeon | |
| dc.title | A Skin Segmentation Method for touchless image viewer in the operating room by 2D camera | |
| dc.type | Conference paper | |
| dc.rights.holder | Scopus | |
| dc.identifier.bibliograpycitation | 2023 3rd International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics, ICA-SYMP 2023. Vol , No. (2023), p.29-32 | |
| dc.identifier.doi | 10.1109/ICA-SYMP56348.2023.10044930 | |
| Appears in Collections: | Scopus 2023 | |
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