Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches
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 c...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2013-01-01
|
| Series: | Terrestrial, Atmospheric and Oceanic Sciences |
| Subjects: | |
| Online Access: |
http://tao.cgu.org.tw/images/attachments/v245p773.pdf
|
| _version_ | 1818483273739796480 |
|---|---|
| author | Hung-Ming Kao Hsuan Ren Chao-Shing Lee Yen-Liang Chen Yen-Shuo Lin Yeng Su |
| author_facet | Hung-Ming Kao Hsuan Ren Chao-Shing Lee Yen-Liang Chen Yen-Shuo Lin Yeng Su |
| author_sort | Hung-Ming Kao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T11:58:07Z |
| format | Article |
| id | doaj.art-9baaf83b0f314adf9b98432dfb2faed8 |
| institution | Directory Open Access Journal |
| issn | 1017-0839 2311-7680 |
| language | English |
| last_indexed | 2024-12-10T11:58:07Z |
| publishDate | 2013-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Terrestrial, Atmospheric and Oceanic Sciences |
| spelling | doaj.art-9baaf83b0f314adf9b98432dfb2faed82022-12-22T01:49:42ZengSpringerTerrestrial, Atmospheric and Oceanic Sciences1017-08392311-76802013-01-0124577310.3319/TAO.2013.04.29.01(T)1174Monitoring Debris Flows Using Spatial Filtering and Entropy Determination ApproachesHung-Ming KaoHsuan RenChao-Shing LeeYen-Liang ChenYen-Shuo LinYeng SuWe 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. http://tao.cgu.org.tw/images/attachments/v245p773.pdf LandslideDebris flowWarming systemRemote sensingCameraVideoSpatial filterEntropy determination |
| spellingShingle | Hung-Ming Kao Hsuan Ren Chao-Shing Lee Yen-Liang Chen Yen-Shuo Lin Yeng Su Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches Terrestrial, Atmospheric and Oceanic Sciences Landslide Debris flow Warming system Remote sensing Camera Video Spatial filter Entropy determination |
| title | Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches |
| title_full | Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches |
| title_fullStr | Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches |
| title_full_unstemmed | Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches |
| title_short | Monitoring Debris Flows Using Spatial Filtering and Entropy Determination Approaches |
| title_sort | monitoring debris flows using spatial filtering and entropy determination approaches |
| topic | Landslide Debris flow Warming system Remote sensing Camera Video Spatial filter Entropy determination |
| url |
http://tao.cgu.org.tw/images/attachments/v245p773.pdf
|
| work_keys_str_mv | AT hungmingkao monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches AT hsuanren monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches AT chaoshinglee monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches AT yenliangchen monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches AT yenshuolin monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches AT yengsu monitoringdebrisflowsusingspatialfilteringandentropydeterminationapproaches |