Mathematical Analysis of Image Matching Techniques

• URL: http://arxiv.org/abs/2604.07574v1
• Date: Wed, 08 Apr 2026 20:24:40 GMT
• Title: Mathematical Analysis of Image Matching Techniques
• Abstract summary: The study uses a manually constructed dataset of GPS-annotated satellite image tiles with intentional overlaps.<n>We examine the impact of the number of extracted keypoints on the resulting Inlier Ratio.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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