Image matching by affine speed-up robust features

Chen Lin; Jin Liu; Liang Cao

doi:10.1117/12.900333

2 December 2011 Image matching by affine speed-up robust features

Chen Lin, Jin Liu, Liang Cao

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040G (2011) https://doi.org/10.1117/12.900333
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Affine invariant image comparison is always consequential in computer vision. In this paper, affine-SURF (ASURF) is introduced. Through a series of affine transformations and feature extraction, the matching algorithm becomes more robust with the view and scale change. A kd-tree structure is build to store the feature sets and BBF search algorithm is used in feature matching, then duplicates are removed by the conditional of Euclidean distance ratio. Experiments show it has a good result, comparisons with SIFT and SURF is made to prove its performance.

Citation Download Citation

Chen Lin, Jin Liu, and Liang Cao "Image matching by affine speed-up robust features", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040G (2 December 2011); https://doi.org/10.1117/12.900333

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available