By Topic

Image transformation approach to nonlinear shape restoration

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)
Tang, Y.Y. ; Centre for Pattern Recognition & Machine Intelligence, Concordia Univ., Montreal, Que., Canada ; Suen, C.Y.

Nonlinear shape distortions are considered as uncertainty in computer vision, robot vision, and pattern recognition. A new approach to nonlinear shape restoration based on nonlinear image shape transformation is proposed. The principal idea of this method is that two-dimensional (2-D) transformation is used to approximate a three-dimensional (3-D) problem. Five particular image transformation models, bilinear, quadratic, cubic, biquadratic, and bicubic models, are presented in this paper to handle some special cases. Two general transformation models, Coons and harmonic models, are also introduced to tackle more general and more complicated problems. These models are derived from finite-element theory and they can be used to approximate some nonlinear shape distortions under certain conditions. Furthermore, their inverse transformations can be used to remove nonlinear shape distortions. Some useful algorithms are developed. The performance of the proposed approach for nonlinear shape restoration has been evaluated in several experiments with interesting results

Published in:

Systems, Man and Cybernetics, IEEE Transactions on  (Volume:23 ,  Issue: 1 )