Rotation invariant feature lines transform for image matching-Reference-Cited by-同舟云学术

Rotation invariant feature lines transform for image matching

Published:2014-09-05 Issue:5 Volume:23 Page:053002
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:en
Short-container-title:J. Electron. Imaging

Author:

Ye Zhang¹,Hongsong Qu²

Affiliation:

1. Changchun Institute of Optics, Fine Mechanics and Physics, Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences, Changchun, ChinabChangchun Institute of Optics, Fine Mechanics and Physics, National & Local United Enginee

2. Changchun Institute of Optics, Fine Mechanics and Physics, National & Local United Engineering Research Center of Small Satellite Technology, Chinese Academy of Sciences, Changchun, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Reference21 articles.

1. A performance evaluation of local descriptors;Mikolajczyk,2005

2. Object recognition from local scale-invariant features;Lowe,1999

3. Distinctive Image Features from Scale-Invariant Keypoints

4. A new framework for feature descriptor based on SIFT

5. Improved algorithm for SIFT feature extraction and matching;Luan,2011

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