Monitoring debris flows using spatial filtering and entropy determination approaches

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/101201

Title:	Monitoring debris flows using spatial filtering and entropy determination approaches
Authors:	任玄;Kao, Hung-Ming;Ren, Hsuan;Lee, Chao-Shing;Chen, Yen-Liang;Lin, Yen-Shuo;Su, Yeng
Contributors:	太空及遙測研究中心
Keywords:	Algorithms;Camera;Color;Colour;Computation;Computer applications;Creeks & streams;Debris flow;Detection;Detritus;Entropy;Entropy determination;Error detection;Landslide;Landslides & mudslides;Moving object recognition;Performance enhancement;Properties;Remote sensing;Spatial filter;Spatial filtering;Subtraction;Video;Warming system;Warning systems
Date:	2013-10-01
Issue Date:	2026-04-21 14:27:02 (UTC+8)
Publisher:	Chinese Geoscience Union;Taiwan: 中華民國地球科學學會
Abstract:	摘要： We developed an automatic debris flow warning system in this study. The system uses a fixed video camera mounted over mountainous streams with a high risk for debris flows. The focus of this study is to develop an automatic algorithm for detecting debris flows with a low computational effort which can facilitate real-time implementation. The algorithm is based on a moving object detection technique to detect debris flow by comparing among video frames. Background subtraction is the kernel of the algorithm to reduce the computational effort, but non-rigid properties and color similarity of the object and the background color introduces some difficulties. Therefore, we used several spatial filtering approaches to increase the performance of the background subtraction. To increase the accuracy entropy is used with histogram analysis to identify whether a debris flow occurred. The modified background subtraction approach using spatial filtering and entropy determination is adopted to overcome the error in moving detection caused by non-rigid and similarities in color properties. The results of this study show that the approach described here can improve performance and also reduce the computational effort. 出版者： Taiwan: 中華民國地球科學學會出版日期： 2013-10-01 出處： TAO : Terrestrial, atmospheric, and oceanic sciences, 2013-10, Vol.24 (5), p.773-791 資源來源：華藝CEPS中文電子期刊服務版權： 2013. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 識別號： ISSN: 1017-0839 識別號： ISSN: 2223-8964 識別號： ISSN: 2311-7680 識別號： EISSN: 2311-7680 識別號： DOI: 10.3319/TAO.2013.04.29.01(T)
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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