吉林大学学报（理学版）2018，Vol.56Issue(1)：82-88,7.DOI:10.13413/j.cnki.jdxblxb.2018.01.14
基于图像梯度信息强化的SIFT特征匹配算法改进
Improvement of SIFT Feature Matching Algorithm Based on Image Gradient Information Enhancement
摘要
Abstract
Aiming at the problem of low matching rate of traditional feature matching algorithms ,we proposed an improved algorithm based on enhanced image gradient information for scale-invariant feature transform (SIFT ) feature matching algorithm . Firstly ,a gradient image was obtained by proper gradient operator .Secondly ,the gradient image and the original image were fused with the specific weight , and after normalization , the fused image was blurred by Gauss . Finally , the traditional algorithm was used for feature extraction .Experimental results show that the visual angle and invariability of rotation of the improved algorithm are obviously better than those of the original algorithm ,and the matching rate of the images with larger brightness or noise is also slightly improved ,w hich effectively improves the accuracy of the SIFT feature matching algorithm .关键词
尺度不变特征转换/特征匹配/局部特征/梯度Key words
scale-invariant feature transform (SIFT )/feature matching/local feature/gradient分类
信息技术与安全科学引用本文复制引用
孙健钧,赵岩,王世刚..基于图像梯度信息强化的SIFT特征匹配算法改进[J].吉林大学学报（理学版）,2018,56(1):82-88,7.基金项目
国家自然科学基金(批准号:61271315)、国家自然科学基金重大项目(批准号:61631009)和吉林省科技发展计划项目(批准号:20150204006GX). （批准号:61271315）
