A Correspondence-Based Software Toolkit for Image Registration

Chia-Ling Tsai, Charles V. Stewart, A. G. Amitha Perera, Ying-Lin Lee, Gehua Yang, Michal Sofka

Abstract: This paper presents a correspondence-based toolkit for image registration. Written in C++, the toolkit complements the capabilities of the insight toolkit (ITK). Major components include features, feature sets, match generators, error scale estimators, robust transformation estimators, and convergence testers, all combined and controlled by several different registration engines. Correspondence-based algorithms which can be implemented using the toolkit extend from ICP to hybrids of intensity-based and feature-based registration. The toolkit is being used both as an education tool and the foundation for developing new algorithms.