Abstract
An improved SSDA (sequential similarity detection algorithm), which may be used to determine similarity in a more efficient manner than the SSDA currently in use, is introduced. The algorithm saves computation time and improves performance compared to the current SSDA. The problem of target tracking, used as an example, and calculation of performance indexes of SSDA are introduced to optimally implement the algorithm. Two series of frame images are simulated from real data to demonstrate the efficiency of the improved SSDA for target tracking. >
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