@inproceedings{f381662d6db048399fdc6263b842f523,
title = "Leakage Detection Using Ground Penetrating Radar C-Scan Based on 3D Fuzzy C-Means Clustering",
abstract = "This paper presents an unsupervised change detection approach for underground leakage detection using ground penetrating radar (GPR) C-scan images. Superpixel and 3D fuzzy c-means are introduced in difference image(DI) generation and classification processes. Converting DI into superpixels reduces the negative influence of local random noise. The fuzzy c means algorithm was reformulated by introducing a spatial factor to involve 3D neighborhood information among adjacent slices. Experiments on field data demonstrate that the proposed algorithm has good capability to detect leakage areas in time series measurements.",
keywords = "3D Fuzzy c-means, Change Detection, GPR C-scan",
author = "Yimin Zhou and Lai, {Wallace Wai Lok}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 12th International Workshop on Advanced Ground Penetrating Radar, IWAGPR 2023 ; Conference date: 05-07-2023 Through 07-07-2023",
year = "2023",
doi = "10.1109/IWAGPR57138.2023.10329148",
language = "English",
series = "2023 12th International Workshop on Advanced Ground Penetrating Radar, IWAGPR 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 12th International Workshop on Advanced Ground Penetrating Radar, IWAGPR 2023",
}