网络安全与数据治理2026，Vol.45Issue(3)：33-39,7.DOI:10.19358/j.issn.2097-1788.2026.03.005
面向非刚性形变图像的关键点匹配方法
Key point matching method for non-rigid deformed images
摘要
Abstract
Non-rigid deformations significantly impair the performance of traditional keypoint matching algorithms in image matching tasks,re-sulting in reduced matching accuracy.To address this issue,a matching method based on probabilistic modeling and feature enhancement is proposed.First,an adaptive keypoint sampling strategy is designed to resolve the redundancy in keypoint distribution under complex deforma-tions by employing dynamic spatial constraints and boundary-aware filtering.Second,to overcome the limitation where deterministic geometric transformation estimation tends to fall into local optima,a Student-t distribution is introduced to model the uncertainty of geometric transforma-tion parameters,thereby enhancing descriptor adaptability in complex deformation scenarios.Finally,a feature enhancement module based on Gaussian priors is constructed.This module utilizes direction-sensitive operators to reinforce key structural information,effectively mitigating feature drift caused by non-rigid deformations.Experimental results demonstrate that the proposed method effectively improves matching accura-cy for non-rigid images and exhibits superior robustness in scenarios involving complex non-rigid deformations.关键词
非刚性图像匹配/关键点检测/不确定性建模/特征增强Key words
non-rigid image matching/keypoint detection/uncertainty modeling/feature enhancement分类
信息技术与安全科学引用本文复制引用
董家麟,吴丽君..面向非刚性形变图像的关键点匹配方法[J].网络安全与数据治理,2026,45(3):33-39,7.基金项目
国家自然科学基金(62271151,W2421092) （62271151,W2421092）
