Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms
Due to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this proble...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/1793212 |
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| _version_ | 1849405733100060672 |
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| author | Liang Huang Xueqin Yu Xiaoqing Zuo |
| author_facet | Liang Huang Xueqin Yu Xiaoqing Zuo |
| author_sort | Liang Huang |
| collection | DOAJ |
| description | Due to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. Then, Zernike moments are applied to carry out edge detection on the remote sensing images clustered. Finally, visual comparison and sensitivity methods are adopted to evaluate the accuracy of the edge information detected. Afterwards, two groups of experimental data are selected to verify the proposed method. Results show that the proposed method effectively improves the accuracy of edge information extracted from remote sensing images. |
| format | Article |
| id | doaj-art-49bd38f5401c4ab2bdb8c87896e8aeb0 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-49bd38f5401c4ab2bdb8c87896e8aeb02025-08-20T03:36:35ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742017-01-01201710.1155/2017/17932121793212Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering AlgorithmsLiang Huang0Xueqin Yu1Xiaoqing Zuo2Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, ChinaKunming Surveying and Mapping Institute, Kunming 650051, ChinaFaculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, ChinaDue to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. Then, Zernike moments are applied to carry out edge detection on the remote sensing images clustered. Finally, visual comparison and sensitivity methods are adopted to evaluate the accuracy of the edge information detected. Afterwards, two groups of experimental data are selected to verify the proposed method. Results show that the proposed method effectively improves the accuracy of edge information extracted from remote sensing images.http://dx.doi.org/10.1155/2017/1793212 |
| spellingShingle | Liang Huang Xueqin Yu Xiaoqing Zuo Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms International Journal of Aerospace Engineering |
| title | Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms |
| title_full | Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms |
| title_fullStr | Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms |
| title_full_unstemmed | Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms |
| title_short | Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms |
| title_sort | edge detection in uav remote sensing images using the method integrating zernike moments with clustering algorithms |
| url | http://dx.doi.org/10.1155/2017/1793212 |
| work_keys_str_mv | AT lianghuang edgedetectioninuavremotesensingimagesusingthemethodintegratingzernikemomentswithclusteringalgorithms AT xueqinyu edgedetectioninuavremotesensingimagesusingthemethodintegratingzernikemomentswithclusteringalgorithms AT xiaoqingzuo edgedetectioninuavremotesensingimagesusingthemethodintegratingzernikemomentswithclusteringalgorithms |