Undistortion methods based on perspective invariants play an important role in computer vision. The key of these
methods is how to choose an proper measure to describe the perspective invariance of undistorted image features. We
propose a new measure based on the homography between the control points in undistorted image and the pattern. The
less the distortion is, the less the mapping error is. A new lens distortion calibration method is also put forward which
uses this measure to search for accurate distortion parameters by iterative optimization. Comparing with other proposed
measures based on perspective invariants, our measure is both concise and comprehensive. Both synthetic and real
experiments show that our method performs well in accuracy and runtime.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.