摘要
SIFT算法和SURF算法是图像特征提取和匹配的典型方法,广泛应用于目标检测、图像理解与识别等领域,然而对二者尚缺乏较深入的对比研究。针对这两种算法,采用实验室相机实拍图像和低空无人机实拍图像,以不同的图像旋转角度进行特征点提取和图像匹配实验,从匹配成功率和运行效率两个方面对算法的性能进行对比研究。结果表明,SIFT算法具有较好的图像旋转不变性,匹配精度较高,而SURF算法匹配精度较低,但是效率较高,因此在实际应用中可根据具体需求合理选择。
The SIFT and SURF algorithms as two typical algorithms for image feature extraction and matching are widely used in the fields of target detection,image understanding and recognition,but the comparison research on the two algorithms is shallow.In allusion to the two algorithms,the feature point extraction and image matching experiment for the images taken by laboratory camera and UVA are carried out according to different image rotation angles.The performances of the two algorithms are compared in the aspects of matching success rate and operating efficiency.The results show that the SIFT algorithm has perfect image rotation invariance and high matching accuracy,and the SURF algorithm has low matching accuracy and high efficiency.One of the two algorithms can be selected reasonably according to the specific requirements.
作者
陈敏
汤晓安
CHEN Min;TANG Xiaoan(School of Electronic Information,Hunan Institute of Information Technology,Changsha 410151,China;College of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China)
出处
《现代电子技术》
北大核心
2018年第7期41-44,共4页
Modern Electronics Technique
基金
国家自然科学基金项目资助(61375033)~~
关键词
SIFT
SURF
性能对比
特征提取
图像匹配
算法效率
SIFT
SURF
performance comparison
feature extraction
image matching
algorithm efficiency
