Threshold Determination for BIM User Image Segmentation Using Fuzzy C-Means for Development of Adaptive BIM

Santosa, Stefanus and Pana, Sudirman S. and Setiadi, De R. M. and Satito, Aryo and Ardjo, Anwar S. and Santosa, Yonathan Purbo (2021) Threshold Determination for BIM User Image Segmentation Using Fuzzy C-Means for Development of Adaptive BIM. Proceedings of the International Conference on Innovation in Science and Technology (ICIST 2020), 208. ISSN 2352-5401

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The Building Information Modeling (BIM) Repository is required to adapt to its users who access BIM objects independently through the Common Data Environment (CDE). BIM objects are not always easy for all users to understand and misperceptions may occur due to users’ varying abilities and learning styles. The solution can be done through the Intelligent Monitoring System (IMS) based learning technology to perform a visual analysis of BIM users. One important issue in the visual tracking system is the degradation of the model caused by inaccuracies in determining the segmentation threshold between the user’s foreground and background images. Segmentation is still difficult when performed on complex images that have a lot of noise, inhomogeneity intensity, textures, or multi-phase structures. The focus of this research is to determine the threshold value using the Fuzzy C-Mean (FCM) approach which is compared with the performance of the Otsu method. Results showed that FCM has a smaller error rate than the Otsu method, 1.15E + 02 perframe compared to 5.11E + 02. FCM processing time is longer than Otsu, 3.6057 units of time perframe compared to 0.0331. We hope that this research can be used to development of an adaptive BIM Repository.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 004 Data processing & computer science
500 Science > 510 Mathematics
Divisions: Journal Publication
Depositing User: Mr Yonathan Purbo Santosa
Date Deposited: 02 Nov 2022 23:37
Last Modified: 24 Jul 2023 00:41

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