Target tracking in infrared imagery using weighted composite reference function-based decision fusion

Author

Dawoud, Amer ; Alam, M.S. ; Bal, A. ; Loo, C.

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of South Alabama, Mobile, AL, USA

Volume

15

Issue

2

fYear

2006

Firstpage

404

Lastpage

410

Abstract

In this paper, we propose a novel decision fusion algorithm for target tracking in forward-looking infrared image sequences recorded from an airborne platform. An important part of this study is identifying the failure modes in this type of imagery. Our strategy is to prevent these failure modes from developing into tracking failures. The results furnished by competing ego-motion compensation and tracking algorithms are evaluated based on their similarity to a target model constructed using the weighted composite reference function.

Keywords

image sequences; infrared imaging; motion compensation; target tracking; airborne platform; decision fusion; ego motion compensation; infrared image sequences; target tracking; weighted composite reference function; Hidden Markov models; Image edge detection; Image sensors; Image sequences; Infrared image sensors; Infrared imaging; Mobile computing; Pattern recognition; Signal to noise ratio; Target tracking; Decision fusion; forward-looking infrared (FLIR); target tracking (TT); weighted composite reference function (WCRF); Algorithms; Artificial Intelligence; Cluster Analysis; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Infrared Rays; Motion; Pattern Recognition, Automated; Subtraction Technique; Video Recording;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2005.860626

Filename

1576813