Advanced Image and Video Retrieval Techniques
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Abstract
Abstract
Image registration is essential in applications such as electronic image stabilization. Scale-Invariant Feature Transform (SIFT), a widely used local keypoint detector and descriptor, typically provides accurate registration; however, it often fails in scenes with strong linear structures (e.g., shutters), where local features become ambiguous. We propose Hough-SIFT, a robust registration method that performs SIFT descriptor matching in Hough space. In this domain, linear structures form distinctive peaks that restore descriptor discriminability. Experiments demonstrate that Hough-SIFT is robust in linear scenes where SIFT frequently fails, while maintaining accuracy comparable to SIFT in normal scenes.
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@article{Satoh2026Hough,
title = {Hough-SIFT: Robust Image Registration for Linear Structures via Hough Space},
author = {Masaki Satoh},
journal = {arXiv (Cornell University)},
year = {2026},
url = {https://arxiv.org/abs/2607.14598}
}FAQ
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