Automatic keypoints extraction from UAV image with refine and improved scale invariant features transform (RI-SIFT) Article Swipe
Hayder Dibs
,
Mohammed Oludare Idrees
,
Vahideh Saeidi
,
Shattri Mansor
·
YOU?
·
· 2016
· Open Access
·
YOU?
·
· 2016
· Open Access
·
In this study, the performance of Refine and Improved Scale Invariant Features Transform (RI-SIFT) recently developed and patented to automatically extract key points from UAV images was examined. First the RI- SIFT algorithm was used to detect and extract CPs from two overlapping UAV images. To evaluate the performance of RI-SIFT, the original SIFT which employs nearest neighbour (NN) algorithms was used to extract keypoints from the same adjacent UA V images. Finally, the quality of the points extracted with RI- SIFT was evaluated by feeding them into polynomial, adjust, and spline transform mosaicing algorithms to stitch the images. The result indicates that RI-SIFT performed better than SIFT and NN with 271, 1415, and 1557points extracted respectively. Also, spline transform gives the most accurate mosaicked image with subpixel RMSE value of 1.0925 pixels equivalent to 0.10051m, followed by adjust transform with root mean square error (RSME) value of 1.956821 pixel (0.17611m) while polynomial transform produced the least accuracy result.
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- Type
- article
- Language
- en
- http://psasir.upm.edu.my/id/eprint/55178/1/Automatic%20keypoints%20extraction%20from%20UAV%20image%20with%20refine%20and%20improved%20scale%20invariant%20features%20transform%20%28RI-SIFT%29.pdf
- OA Status
- green
- Cited By
- 5
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2781253110
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2781253110Canonical identifier for this work in OpenAlex
- Title
-
Automatic keypoints extraction from UAV image with refine and improved scale invariant features transform (RI-SIFT)Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-01-01Full publication date if available
- Authors
-
Hayder Dibs, Mohammed Oludare Idrees, Vahideh Saeidi, Shattri MansorList of authors in order
- PDF URL
-
https://psasir.upm.edu.my/id/eprint/55178/1/Automatic%20keypoints%20extraction%20from%20UAV%20image%20with%20refine%20and%20improved%20scale%20invariant%20features%20transform%20%28RI-SIFT%29.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://psasir.upm.edu.my/id/eprint/55178/1/Automatic%20keypoints%20extraction%20from%20UAV%20image%20with%20refine%20and%20improved%20scale%20invariant%20features%20transform%20%28RI-SIFT%29.pdfDirect OA link when available
- Concepts
-
Scale-invariant feature transform, Subpixel rendering, Artificial intelligence, Pixel, Hough transform, Pattern recognition (psychology), Computer vision, Mathematics, Spline (mechanical), Computer science, Feature extraction, Image (mathematics), Engineering, Structural engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1, 2022: 1, 2021: 1, 2020: 1, 2019: 1Per-year citation counts (last 5 years)
- Related works (count)
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20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.algorithm | 32 |
| abstract_inverted_index.developed | 15 |
| abstract_inverted_index.evaluated | 83 |
| abstract_inverted_index.examined. | 27 |
| abstract_inverted_index.extracted | 78, 115 |
| abstract_inverted_index.indicates | 101 |
| abstract_inverted_index.keypoints | 64 |
| abstract_inverted_index.mosaicing | 93 |
| abstract_inverted_index.mosaicked | 124 |
| abstract_inverted_index.neighbour | 57 |
| abstract_inverted_index.performed | 104 |
| abstract_inverted_index.transform | 92, 119, 139, 153 |
| abstract_inverted_index.(0.17611m) | 150 |
| abstract_inverted_index.1557points | 114 |
| abstract_inverted_index.algorithms | 59, 94 |
| abstract_inverted_index.equivalent | 133 |
| abstract_inverted_index.polynomial | 152 |
| abstract_inverted_index.overlapping | 42 |
| abstract_inverted_index.performance | 4, 48 |
| abstract_inverted_index.polynomial, | 88 |
| abstract_inverted_index.automatically | 19 |
| abstract_inverted_index.respectively. | 116 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.65271046 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |