NDLI: SRP-AKAZE: an improved accelerated KAZE algorithm based on sparse random projection

Content Provider	IET Digital Library
Author	Li, Dan Xu, Qiannan Yu, Wennian Wang, Bing
Abstract	The AKAZE algorithm is a typical image registration algorithm that has the advantage of high computational efficiency based on non-linear diffusion. However, it is weaker than the scale-invariant feature transformation (SIFT) algorithm in terms of robustness and stability. We propose a new and improved version of the AKAZE algorithm by using the SIFT descriptor based on sparse random projection (SRP). The proposed method not only retains the advantage of high efficiency of the AKAZE algorithm in feature detection but also has the stability of the SIFT descriptor. Moreover, the computational complexity due to the high dimension of the SIFT descriptor, which limits the speed of feature matching, is drastically reduced by the SRP strategy. Experiments on several benchmark image datasets demonstrate that the proposed algorithm can significantly improve the stability of the AKAZE algorithm, and the results suggest the better matching performance and robustness of the feature descriptor.
Starting Page	131
Ending Page	137
Page Count	7
ISSN	17519632
Volume Number	14
e-ISSN	17519640
Issue Number	Issue 4, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/14/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2019.0622
Journal	IET Computer Vision
Publisher Date	2020-04-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AKAZE Algorithm Computer Vision And Image Processing Technique Feature Descriptor Feature Extraction High Computational Efficiency Image Matching Image Recognition Image Registration Image Resolution Improved Accelerated KAZE Algorithm New Version Nonlinear Diffusion Nonlinear Filter Optical, Image And Video Signal Processing Pipeline Processing Scale-invariant Feature Transformation Algorithm SIFT Descriptor Sparse Random Projection SRP-AKAZE Transform Typical Image Registration Algorithm VLSI
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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