Mathematical Analysis of Image Matching Techniques
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866913016725897216 |
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| author | Samoilenko, Oleh |
| author_facet | Samoilenko, Oleh |
| contents | Image matching is a fundamental problem in Computer Vision with direct applications in robotics, remote sensing, and geospatial data analysis. We present an analytical and experimental evaluation of classical local feature-based image matching algorithms on satellite imagery, focusing on the Scale-Invariant Feature Transform (SIFT) and the Oriented FAST and Rotated BRIEF (ORB). Each method is evaluated through a common pipeline: keypoint detection, descriptor extraction, descriptor matching, and geometric verification via RANSAC with homography estimation. Matching quality is assessed using the Inlier Ratio - the fraction of correspondences consistent with the estimated homography. The study uses a manually constructed dataset of GPS-annotated satellite image tiles with intentional overlaps. We examine the impact of the number of extracted keypoints on the resulting Inlier Ratio. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_07574 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Mathematical Analysis of Image Matching Techniques Samoilenko, Oleh Computer Vision and Pattern Recognition Numerical Analysis 68T45, 68U10, 65D19 Image matching is a fundamental problem in Computer Vision with direct applications in robotics, remote sensing, and geospatial data analysis. We present an analytical and experimental evaluation of classical local feature-based image matching algorithms on satellite imagery, focusing on the Scale-Invariant Feature Transform (SIFT) and the Oriented FAST and Rotated BRIEF (ORB). Each method is evaluated through a common pipeline: keypoint detection, descriptor extraction, descriptor matching, and geometric verification via RANSAC with homography estimation. Matching quality is assessed using the Inlier Ratio - the fraction of correspondences consistent with the estimated homography. The study uses a manually constructed dataset of GPS-annotated satellite image tiles with intentional overlaps. We examine the impact of the number of extracted keypoints on the resulting Inlier Ratio. |
| title | Mathematical Analysis of Image Matching Techniques |
| topic | Computer Vision and Pattern Recognition Numerical Analysis 68T45, 68U10, 65D19 |
| url | https://arxiv.org/abs/2604.07574 |