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Proceedings Paper

Image matching by affine speed-up robust features
Author(s): Chen Lin; Jin Liu; Liang Cao
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Paper 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.

Paper Details

Date Published: 2 December 2011
PDF: 5 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040G (2 December 2011); doi: 10.1117/12.900333
Show Author Affiliations
Chen Lin, Wuhan Univ. (China)
Jin Liu, Wuhan Univ. (China)
Liang Cao, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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