Panoramic image matching method for UAV remote sensing based of sift algorithm
TA1637.E47 2014
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| Format: | text::Final Year Project |
| Language: | en_US |
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2024
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| _version_ | 1838943489301151744 |
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| author | Emran Izzuddin Mohd Suib |
| author_facet | Emran Izzuddin Mohd Suib |
| author_sort | Emran Izzuddin Mohd Suib |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | TA1637.E47 2014 |
| format | Resource Types::text::Final Year Project |
| id | my.uniten.dspace-33127 |
| institution | Universiti Tenaga Nasional |
| language | en_US |
| publishDate | 2024 |
| record_format | dspace |
| spelling | my.uniten.dspace-331272025-07-28T12:17:13Z Panoramic image matching method for UAV remote sensing based of sift algorithm Emran Izzuddin Mohd Suib Vehicles Image processing TA1637.E47 2014 Unmanned Aerial Vehicles (UAVs) are usually equipped with payloads that include multispectral digital cameras. These cameras provide operators the opportunity to monitor terrain, carry out reconnaissance mission from a distant ground station without endangering UAV operators or commonly known as remote sensing. Remote sensing technology on UAVS is widely used in today's surveillance system, however there are technical challenges that exist. The problem often arises where large sequences or sets images taken from the UAV cameras that being send and received by the operators on the ground station are too many, field-of-view (FOV) of a single image is very limited and can cause the operators to become overwhelmed to identify the images. This problem can be rendered down by implementing Scale Invariant Feature Transform (SIFT) algorithm on the images so that operators can analyze the images more efficiently. In this paper, SIFT algorithm will be simulated in MATLAB to show its capability in solving the FOV issues by stitching and matching the images because of its robustness and accuracy in extracting keypoints. Finally, satisfactory results are obtained. 2024-07-31T08:02:55Z 2024-07-31T08:02:55Z 2014 Resource Types::text::Final Year Project https://irepository.uniten.edu.my/handle/123456789/33127 en_US application/pdf |
| spellingShingle | Vehicles Image processing Emran Izzuddin Mohd Suib Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title | Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title_full | Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title_fullStr | Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title_full_unstemmed | Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title_short | Panoramic image matching method for UAV remote sensing based of sift algorithm |
| title_sort | panoramic image matching method for uav remote sensing based of sift algorithm |
| topic | Vehicles Image processing |
| url_provider | http://dspace.uniten.edu.my/ |