Data Registration and Multiple-target tracking (MTT) are an essential requirement for surveillance systems which employs a large number of sensors for information collection and environment interpretation. Prior to integration of the collected information data registration is required to ensure all data are aligned. A data fusion center is a system which integrates information and consists of (1) tracking targets using a Kalman filter and its variations; (2) selecting an adequate target model to describe target maneuvers; (3) using geometric gating scoring to associate measurements (or contacts) to tracks; (4) applying either the Bayesian reasoning method or the Dempster-Shafer theory to integration of information attributed by targets; (5) employing a modified Munkres' algorithm to solve assignment problems caused by conflicts between tracks and hypotheses; (6) implementing clustering techniques to manage hypotheses at a certain level; (7) pruning a set of hypotheses to meet practical limitations. In this research we investigate registration problems and focus on designing and developing computer-aided algorithms for data registration and image fusion such as combining information of images generated by different or dissimliar sensors. Pixel-level fusion, feature level fusion and decision level fusion are of particular interest.
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