Vision-Based Horizon Extraction Method under Kalman Filter Framework
As the demands of UAV's visual navigation technology, we bring out a new horizon extraction method in this paper. Firstly, we propose a horizon extraction algorithm for single image. We employ dark channel in single image to avoid the interferences from clouds and fogs, and use Sobel operator e...
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| Main Authors: | , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2014-09-01.
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| Subjects: | |
| Online Access: | Get fulltext |
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| LEADER | 02319 am a22002893u 4500 | ||
|---|---|---|---|
| 001 | ijeecs3810_2282 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Guan, Zhenyu |e author |
| 700 | 1 | 0 | |a Li, Jie |e author |
| 700 | 1 | 0 | |a Yang, Huan |e author |
| 245 | 0 | 0 | |a Vision-Based Horizon Extraction Method under Kalman Filter Framework |
| 260 | |b Institute of Advanced Engineering and Science, |c 2014-09-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3810 | ||
| 520 | |a As the demands of UAV's visual navigation technology, we bring out a new horizon extraction method in this paper. Firstly, we propose a horizon extraction algorithm for single image. We employ dark channel in single image to avoid the interferences from clouds and fogs, and use Sobel operator extract edges, among which we can extract the true horizon through an algorithm mentioned in Paragraph II. Secondly, we propose a horizon extraction algorithm for video streaming under Kalman Filter (KF) framework based on the horizon extraction algorism for single image. The position of horizon in each frame will be estimated by using the priori horizon positions under KF framework at first, and a search neighborhood will be determined around the estimated position, in which we can get the true position of the horizon through a certain search algorithm. Simulations and analyses are carried out with aerial video streaming, the results show that such algorithms work well on those videos with noise, clouds and fogs, while the time overhead decrease by about 50% than traditional algorithms. | ||
| 540 | |a Copyright (c) 2014 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc-nd/4.0 | ||
| 546 | |a eng | ||
| 690 | |a horizon extraction algorithm; Kalman Filter; video streaming; dark channel | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 12, No 9: September 2014; 6780-6788 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v12.i9 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3810/2282 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3810/2282 |z Get fulltext |