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Department自适应光学技术研究室(八室)
Optimization of SIFT algorithm for fast-image feature extraction in line-scanning ophthalmoscope
He, Yi1,2; Deng, Guohua4; Wang, Yuanyuan1,2,3; Wei, Ling1,2; Yang, Jinsheng1,2; Li, Xiqi1,2; Zhang, Yudong1,2
Source PublicationOPTIK
Volume152Pages:21-28
2018
Language英语
ISSN0030-4026
DOI10.1016/j.ijleo.2017.09.075
Indexed BySCI ; Ei
WOS IDWOS:000418624500004
EI Accession Number20174104243613
SubtypeJ
AbstractThe Scale Invariant Feature Transform (SIFT) algorithm is utilized broadly in image registration to improve image qualities. However, the algorithm's complexity reduces its efficiency in biology study and usually requires real-time. In this article, we present an improved SIFT technique in software architecture for matching sequences of images taken from a line-scanning ophthalmoscope (LSO). The method generates the Gaussian Scale-space pyramid in frequency domain to complete the SIFT feature detector more quickly. A novel SIFT descriptor invariable with rotation and illumination is then created to reduce calculation time, implementing the original SIFT method, our improved SIFT method, and the graphic processing unit (GPU) version of our improved SIFT method. The experiments have shown that the improved SIFT is almost 2-3 times faster than the original while maintaining more robust performance, and the GPU implementation of the improved SIFT is 20 times faster than central processing unit (CPU) implementation and achieves acceleration at real-time as expected. Although tested on an LSO system, the improved SIFT method does not rely on the acquisition setup. As a result, this method can be applied to other imaging instruments, e.g., adaptive optics to increase their resolution in agreement. (C) 2017 Elsevier GmbH. All rights reserved.
KeywordConfocal microscopy Retina scanning Medical and biological imaging Feature extraction Image matching SIFT
WOS KeywordMOTION CORRECTION ; HIGH-SPEED ; REGISTRATION
EI KeywordsAdaptive optics ; Computational complexity ; Confocal microscopy ; Extraction ; Feature extraction ; Frequency domain analysis ; Graphics processing unit ; Image matching ; Medical imaging ; Program processors ; Scanning
EI Classification Number721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory ; 741.1 Light/Optics ; 741.3 Optical Devices and Systems ; 746 Imaging Techniques ; 802.3 Chemical Operations ; 921.3 Mathematical Transformations
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/9350
Collection自适应光学技术研究室(八室)
Affiliation1.The Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu; 610209, China;
2.Institute of Optics and Electronic, Chinese Academy of Sciences, Chengdu; 610209, China;
3.School of Optometry and Ophthalmology and Eye Hospital, Wenzhou Medical College, Wenzhou; 325035, China;
4.Department of Ophthalmology, The Third People's Hospital of Changzhou, Jiangsu, China
Recommended Citation
GB/T 7714
He, Yi,Deng, Guohua,Wang, Yuanyuan,et al. Optimization of SIFT algorithm for fast-image feature extraction in line-scanning ophthalmoscope[J]. OPTIK,2018,152:21-28.
APA He, Yi.,Deng, Guohua.,Wang, Yuanyuan.,Wei, Ling.,Yang, Jinsheng.,...&Zhang, Yudong.(2018).Optimization of SIFT algorithm for fast-image feature extraction in line-scanning ophthalmoscope.OPTIK,152,21-28.
MLA He, Yi,et al."Optimization of SIFT algorithm for fast-image feature extraction in line-scanning ophthalmoscope".OPTIK 152(2018):21-28.
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