By Topic

Using Local Affine Invariants to Improve Image Matching

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Fleck, D. ; Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA ; Duric, Z.

A method to classify tentative feature matches as inliers or outliers to a transformation model is presented. It is well known that ratios of areas of corresponding shapes are affine invariants. Our algorithm uses consistency of ratios of areas in pairs of images to classify matches as inliers or outliers. The method selects four matches within a region, and generates all possible corresponding triangles. All matches are classified as inliers or outliers based on the variance among the ratio of areas of the triangles. The selected inliers are used to compute a homography transformation. We present experimental results showing significant improvements over the baseline RANSAC algorithm for pairs of images from the Zurich Building Database.

Published in:

Pattern Recognition (ICPR), 2010 20th International Conference on

Date of Conference:

23-26 Aug. 2010