|本期目录/Table of Contents|

基于尺度、方向和距离约束的改进SIFT配准方法(PDF)

《纳米技术与精密工程》[ISSN:1672-6030/CN:12-1351/O3]

期数:
2017年1期
页码:
36-43
栏目:
精密测量
出版日期:
2017-01-15

文章信息/Info

Title:
An Improved SIFT Registration Method Based on Scale, Orientation and Distance Constraint
作者:
冷成财12 张海鹏1 张聪炫23 陈震23 于乃功4
1. 南昌航空大学数学与信息科学学院,南昌330063; 2. 南昌航空大学无损检测技术教育部重点实验室,南昌330063; 3. 南昌航空大学测试与光电工程学院,南昌330063; 4. 北京工业大学电子信息与控制工程学院,北京100124
Author(s):
Leng Chengcai12 Zhang Haipeng1 Zhang Congxuan23 Chen Zhen23 Yu Naigong4
1. School of Mathematics and Information Sciences, Nanchang Hangkong University, Nanchang 330063, China; 2. Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang 330063, China; 3. School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang 330063, China; 4. College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
关键词:
图像配准 SIFT 特征提取 特征匹配
Keywords:
image registration SIFT feature extraction feature matching
分类号:
TP391.41
DOI:
10.13494/j.npe.20160054
文献标识码:
A
摘要:
针对SIFT算法在图像配准过程中存在遗漏掉大量的正确匹配对且产生误匹配对等问题,本文提出一种基于尺度、方向和距离约束的改进SIFT配准方法(SODC-SIFT).首先用SIFT算法对图像进行初匹配,利用特征点的尺度和主方向的差异剔除误匹配对;然后用最小二乘法求出两幅图像的几何关系;最后利用距离约束,迭代求解,找出正确匹配对,从而实现图像的精确配准.实验结果表明,本文方法与SIFT算法相比具有较强的鲁棒性,能够提升正确匹配对的数量并提高图像的正确匹配率,增强了算法匹配的精确性.
Abstract:
Traditional SIFT method has certain false matching points and will miss a large number of correct matching points in image registration process. To solve this problem, an improved SIFT algorithm based on scale, orientation and distance constraint (SODC-SIFT) is proposed in this paper. First, the images are matched with original SIFT algorithm, and the scale and orientation joint restriction are used to remove mismatching pairs. Then, the least square method is employed to calculate the geometric relationship between the two images. Finally, iteration is conducted to select the correct matching points by distance constraint, so as to achieve accurate image registration. Experimental results show that the proposed method has greater robustness and achieves more correct matching pairs than the traditional SIFT method. Furthermore, the correct matching rate is increased and the accuracy of the algorithm is enhanced.

参考文献/References

备注/Memo

备注/Memo:
收稿日期: 2016-10-11. 基金项目: 国家自然科学基金资助项目(61363049); 中国博士后第八批特别资助基金资助项目(2015T80155); 江西省自然科学基金资助项目(20161BAB212033); 中国科学院复杂系统管理与控制国家重点实验室开放基金资助项目(20140101); 南昌航空大学无损检测技术教育部重点实验室开放基金资助项目(ZD201429007); 江西省教育厅科学基金资助项目(GJJ150751). 作者简介: 冷成财(1982—),男,博士,讲师. 通讯作者: 冷成财,lcc1632000@163.com.
更新日期/Last Update: 2017-02-28