NDLI: Modified sift descriptor for image matching under interference

Content Provider	IEEE Xplore Digital Library
Author	Cheng-Yuan Tang Yi-Leh Wu Maw-Kae Hor Wen-Hung Wang
Copyright Year	2008
Description	Author affiliation: Dept. of Inf. Manage., Huafan Univ., Shihding (Cheng-Yuan Tang)
Abstract	There remain many difficult problems in computer vision research such as object recognition, three dimensional reconstruction, object tracking, etc. And the basis of solving these problems relies on image matching. The scale invariant feature transform (SIFT) algorithm has been widely used for image matching application. The SIFT algorithm can successfully extract the most descriptive feature points in given input images taken under different viewpoints. However, the performance of the original SIFT algorithm degrades under the influence of noise. We propose to modify the SIFT algorithm to produce better invariant feature points for image matching under noise. We also propose to employ the Earth mover's distance (EMD) as the measurement of similarity between two descriptors. We present extensive experiment results to demonstrate the performance of the proposed methods in image matching under noise.
Starting Page	3294
Ending Page	3300
File Size	1494935
Page Count	7
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620974
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Noise Pixel Image matching Smoothing methods Machine learning Cybernetics matching Feature points SIFT EMD
Content Type	Text
Resource Type	Article

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