Share Email Print
cover

Proceedings Paper

Performance evaluation of SIFT under low light contrast
Author(s): Hao Wang; Songzhi Jin; Xiaodan Wei; Cong Zhang; Ruiguang Hu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

As an excellent method for extracting distinctive invariant features from images, SIFT (scale-invariant feature transform) can effectively resist affine transformation such as translation and rotation of images, and theoretically has better resistance to illumination changes [1]. However, in practical applications the performance of SIFT is always affected by the contrast reduction caused by illumination changes. In this paper, the performance of SIFT under different contrasts is systematically analyzed and evaluated, and a reasonable explanation is given for the reason of SIFT performance change under different illumination conditions. And a SIFT fast matching method based on contrast compression is proposed.

Paper Details

Date Published: 14 February 2020
PDF: 7 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 1143006 (14 February 2020); doi: 10.1117/12.2535592
Show Author Affiliations
Hao Wang, Beijing Aerospace Automatic Control Institute (China)
Songzhi Jin, Beijing Aerospace Automatic Control Institute (China)
Xiaodan Wei, Beijing Aerospace Automatic Control Institute (China)
Cong Zhang, Beijing Aerospace Automatic Control Institute (China)
Ruiguang Hu, Beijing Aerospace Automatic Control Institute (China)


Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray