Image registration guided by particle filter Conference Paper

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Overview

abstract

• Image Registration is a central task to different applications, such as medical image analysis, stereo computer vision, and optical flow estimation. One way to solve this problem consists in using Bayesian Estimation theory. Under this approach, this work introduces a new alternative, based on Particle Filters, which have been previously used to estimate the states of dynamic systems. For this work, we have adapted the Particle Filter to carry out the registration of unimodal and multimodal images, and performed a series of preliminary tests, where the proposed method has proved to be efficient, robust, and easy to implement. © 2009 Springer-Verlag.

authors

• Alba Cadena Francisco Alfonso
• Arce Santana Edgar Román
• Campos Delgado Daniel Ulises

publication date

• 2009-01-01

published in

• Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  Journal

Research

keywords

• Bayesian estimation theory; Dynamic Systems; Medical image analysis; Multi-modal image; Optical flow estimation; Particle filter; Unimodal; Air filters; Bayesian networks; Computer science; Computer vision; Distributed computer systems; Dynamical systems; Nonlinear filtering; Optical flows; Stereo vision; Target tracking; Image registration

Identity

Digital Object Identifier (DOI)

• 10.1007/978-3-642-10331-5_52

Additional Document Info

start page

• 554

end page

• 563

volume

• 5875 LNCS

issue

• PART 1