Automatic target tracking in FLIR image sequences

Moving target tracking is a challenging task and is increasingly becoming important for various applications. In this paper, we have presented target detection and tracking algorithm based on target intensity feature relative to surrounding background, and shape information of target. Proposed automatic target tracking algorithm includes two techniques: intensity variation function (IVF) and template modeling (TM). The intensity variation function is formulated by using target intensity feature while template modeling is based on target shape information. The IVF technique produces the maximum peak value whereas the reference target intensity variation is similar to the candidate target intensity variation. When IVF technique fails, due to background clutter, non-target object or other artifacts, the second technique, template modeling, is triggered by control module. By evaluating the outputs from the IVF and TM techniques, the tracker determines the real coordinates of the target. Performance of the proposed ATT is tested using real life forward-looking infrared (FLIR) image sequences taken from an airborne, moving platform.