Better Global Polynomial Approximation for Image Rectification

When using images to locate objects, there is the problem of correcting for distortion and misalignment in the images. An elegant way of solving this problem is to generate an error correcting function that maps points in an image to their corrected locations. We generate such a function by fitting...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of modelling & simulation Vol. 28; no. 3; pp. 299 - 308
Main Author Ward, C.O.
Format Journal Article
LanguageEnglish
Published Calgary Taylor & Francis 2008
Taylor & Francis Ltd
Subjects
Algorithms
Approximation
Cameras
image rectification
Interpolation
Neural networks
Optical properties
Polynomial approximation
Robotics
Robots
Studies
Vision systems
Webcams
Online AccessGet full text

Cover

More Information
Summary:When using images to locate objects, there is the problem of correcting for distortion and misalignment in the images. An elegant way of solving this problem is to generate an error correcting function that maps points in an image to their corrected locations. We generate such a function by fitting a polynomial to a set of sample points. The objective is to identify a polynomial that passes "sufficiently close" to these points with "good" approximation of intermediate points. In the past, it has been difficult to achieve good global polynomial approximation using only sample points. We report on the development of a global polynomial approximation algorithm for solving this problem.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0228-6203
1925-7082
DOI:10.1080/02286203.2008.11442481