计算机应用 ›› 2019, Vol. 39 ›› Issue (7): 2093-2097.DOI: 10.11772/j.issn.1001-9081.2018122564

• 虚拟现实与多媒体计算 • 上一篇    下一篇

适用于倾斜影像的加速KAZE-SIFT特征提取算法

薄单1,2, 李宗春1, 王晓南2, 乔涵文2   

  1. 1. 信息工程大学 地理空间信息学院, 郑州 450001;
    2. 中国洛阳电子装备试验中心, 河南 洛阳 471003
  • 收稿日期:2019-01-02 修回日期:2019-02-28 发布日期:2019-04-09 出版日期:2019-07-10
  • 通讯作者: 李宗春
  • 作者简介:薄单(1985-),男,安徽太和人,工程师,硕士研究生,主要研究方向:计算机视觉、精密工程测量;李宗春(1973-),男,山东日照人,教授,博士,主要研究方向:精密工程测量、计算机视觉;王晓南(1986-),男,河南内乡人,工程师,主要研究方向:大地测量、工程测量;乔涵文(1993-),女,湖北枣阳人,助理工程师,主要研究方向:大地测量、工程测量。
  • 基金资助:

    国家自然科学基金青年基金资助项目(41701463);河南省科技攻关项目(172102210020)。

Accelerated KAZE-SIFT feature extraction algorithm for oblique images

BO Dan<sup>1,2</sup>, LI Zongchun<sup>1</sup>, WANG Xiaonan<sup>2</sup>, QIAO Hanwen<sup>2</sup>   

  1. 1. Institute of Geospatial Information, Information Engineering University, Zhengzhou Henan 450001, China;
    2. Luoyang Electronic Equipment Testing Center, Luoyang Henan 471003, China
  • Received:2019-01-02 Revised:2019-02-28 Online:2019-04-09 Published:2019-07-10
  • Supported by:

    This work is partially supported by the National Natural Science Foundation of China Youth Foud (41701463), the Key Scientific and Technological Project of Henan Province (172102210020).

摘要:

针对传统正摄影像的特征提取算法处理倾斜影像匹配效果不佳的问题,在已有特征提取算法的基础上,提出了一种适用于倾斜影像的特征提取算法——加速KAZE-尺度不变特征变换(AKAZE-SIFT)算法。首先,为保证特征检测的准确性与独特性,采用充分保留图像轮廓信息的加速KAZE(AKAZE)算子进行特征检测;其次,为提升特征描述的稳定性,采用稳健的尺度不变特征变换(SIFT)算子进行特征描述;然后,依据目标特征向量和候选特征向量间的欧氏距离确定粗匹配点对;最后,采用随机抽样一致性算法进行单应性约束,提高匹配纯度。模拟影像在倾斜摄影条件下的模糊、旋转、亮度、视角和尺度变化,对特征提取算法性能进行评估,实验结果表明,AKAZE-SIFT算法相比SIFT算法和AKAZE算法召回率分别提高了12.8%和5.3%,精准率提高了6.5%和6.1%,F1值提升了13.8%和5.6%;提取效率优于SIFT算法,略逊于AKAZE。AKAZE-SIFT算法具有良好的检测和描述能力,更适用于倾斜影像特征提取。

关键词: 加速KAZE算法, 尺度不变特征变换算法, 倾斜影像, 特征提取, 特征匹配

Abstract:

Concerning that traditional vertical image feature extraction algorithms have poor effect on oblique image matching, a feature extraction algorithm, based on Accelerated KAZE (AKAZE) and Scale Invariant Feature Transform (SIFT) algorithm called AKAZE-SIFT was proposed. Firstly, in order to guarantee the accuracy and distinctiveness of image feature detection, AKAZE operator, which fully preserves the contour information of image, was utilized for feature detection. Secondly, the robust SIFT operator was used to improve the stability of feature description. Thirdly, the rough matching point pairs were determined by the Euclidean distance between object feature point vector and candidate feature point vectors. Finally, the homography constraint was applied to improve the matching purity by random sample consensus algorithm. To evaluate the performance of the feature extraction algorithm, the blur, rotation, brightness, viewpoint and scale changes under the condition of oblique photography were simulated. The experimental results show that compared with SIFT algorithm and AKAZE algorithm, the recall of AKAZE-SIFT is improved by 12.8% and 5.3% respectively, the precision of AKAZE-SIFT is increased by 6.5% and 6.1% respectively, the F1 measure of AKAZE-SIFT is elevated by 13.8% and 5.6% respectively and the efficiency of the proposed algorithm is higher than that of SIFT and slightly worse than that of AKAZE. For the excellent detection and description performance, AKAZE-SIFT algorithm is more suitable for oblique image feature extraction.

Key words: Accelerated KAZE (AKAZE) algorithm, Scale Invariant Feature Transform (SIFT) algorithm, oblique image, feature extraction, feature matching

中图分类号: