NDLI: Based on Statistics of the Gradients the Feature Matching Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Jidong Guo Xueqing Li
Copyright Year	2009
Abstract	The feature matching is the first step of severalcomputer vision duties. In this paper we provide a new feature detect and matching approach based on statistics of the gradients of the feature region. It is extension of the sift algorithm. The algorithm represented in this paper can be used to perform reliable matching to image sequence, which have larger change in 3D viewpoint and change in illumination. The new approach not only describes the local region structure but also statistic orientation histogram of periphery twelve 5X5 sample sub-region. The constructed descriptor has more robust distinguishability to support the following match step. In the matching step, by using polar, symmetry and uniqueness constraints to filter the tentative feature pairs, many outliers are eliminated and the correct feature pairs are obtained in the last step. By comparing with traditional Harris--Correlation matching algorithm as well as theoretical analysis, the algorithm that this article proposed has the higher stability as well as the anti-jamming.
Starting Page	983
Ending Page	987
File Size	1594113
Page Count	5
File Format	PDF
ISBN	9781424435814
DOI	10.1109/ETCS.2009.484
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computer vision Change detection algorithms Stability analysis Image sequences Statistics descriptor vector gradients statistics Histograms Matched filters region structure Lighting Robustness feature matching
Content Type	Text
Resource Type	Article

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