Research on optimization of image fast feature point matching algorithm
Abstract The author studied the feature point extraction and matching based on BRISK and ORB algorithms, experimented with the advantages of both algorithms, and ascertained optimal pyramid layer and inter-layer scale parameters used in features extraction and matching for the same scale image and d...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-10-01
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| Series: | EURASIP Journal on Image and Video Processing |
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| Online Access: | http://link.springer.com/article/10.1186/s13640-018-0354-y |
| _version_ | 1819040620445958144 |
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| author | Manyi Wu |
| author_facet | Manyi Wu |
| author_sort | Manyi Wu |
| collection | DOAJ |
| description | Abstract The author studied the feature point extraction and matching based on BRISK and ORB algorithms, experimented with the advantages of both algorithms, and ascertained optimal pyramid layer and inter-layer scale parameters used in features extraction and matching for the same scale image and different scale images with BRISK and ORB algorithm, and analyzed the effectiveness of different parameters combinations on the accuracies of feature extraction and matching and proposed method to determine parameters based on the results. In addition, comparing with the traditional algorithm, using the optimal algorithm with the parameters combining Gaussian denoising, graying, and image sharpening, the ratio of feature points for detection improved 3%; the number of effective matching points increased by nearly 2%. Meanwhile, an algorithm experiment on UAV image mosaic was carried out. The transition of mosaic image color was more natural, and there was no clear mosaic joint with the stitching effect, which indicated that the optimized parameters and the extracted feature point pairs can be used for matrix operations and the algorithm is suitable for UAV image mosaic processing. |
| first_indexed | 2024-12-21T09:12:00Z |
| format | Article |
| id | doaj.art-e727af2b784f431f825e8ee3330b3b07 |
| institution | Directory Open Access Journal |
| issn | 1687-5281 |
| language | English |
| last_indexed | 2024-12-21T09:12:00Z |
| publishDate | 2018-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-e727af2b784f431f825e8ee3330b3b072022-12-21T19:09:13ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812018-10-012018112710.1186/s13640-018-0354-yResearch on optimization of image fast feature point matching algorithmManyi Wu0School of Geodesy and Geomatics, Wuhan UniversityAbstract The author studied the feature point extraction and matching based on BRISK and ORB algorithms, experimented with the advantages of both algorithms, and ascertained optimal pyramid layer and inter-layer scale parameters used in features extraction and matching for the same scale image and different scale images with BRISK and ORB algorithm, and analyzed the effectiveness of different parameters combinations on the accuracies of feature extraction and matching and proposed method to determine parameters based on the results. In addition, comparing with the traditional algorithm, using the optimal algorithm with the parameters combining Gaussian denoising, graying, and image sharpening, the ratio of feature points for detection improved 3%; the number of effective matching points increased by nearly 2%. Meanwhile, an algorithm experiment on UAV image mosaic was carried out. The transition of mosaic image color was more natural, and there was no clear mosaic joint with the stitching effect, which indicated that the optimized parameters and the extracted feature point pairs can be used for matrix operations and the algorithm is suitable for UAV image mosaic processing.http://link.springer.com/article/10.1186/s13640-018-0354-yBRISK and ORB algorithmFast feature detectionAlgorithm optimizationUAV image mosaic processing |
| spellingShingle | Manyi Wu Research on optimization of image fast feature point matching algorithm EURASIP Journal on Image and Video Processing BRISK and ORB algorithm Fast feature detection Algorithm optimization UAV image mosaic processing |
| title | Research on optimization of image fast feature point matching algorithm |
| title_full | Research on optimization of image fast feature point matching algorithm |
| title_fullStr | Research on optimization of image fast feature point matching algorithm |
| title_full_unstemmed | Research on optimization of image fast feature point matching algorithm |
| title_short | Research on optimization of image fast feature point matching algorithm |
| title_sort | research on optimization of image fast feature point matching algorithm |
| topic | BRISK and ORB algorithm Fast feature detection Algorithm optimization UAV image mosaic processing |
| url | http://link.springer.com/article/10.1186/s13640-018-0354-y |
| work_keys_str_mv | AT manyiwu researchonoptimizationofimagefastfeaturepointmatchingalgorithm |