Abstract
This study presented a novel algorithm, namely, modified flower pollination algorithm (MFPA), for moving object tracking in real time video. Three variables, i.e., x-coordinate, y-coordinate and width, known as search window, were used to represent the features of the target object. The image within the search window was extracted, and used to calculate the Hue, Saturation, and Value (HSV) histogram. The HSV histogram was then used as a feature model of the target object. Subsequently, the MFPA will search for an optimal match of the target using Bhattacharyya distance as the fitness function. Simulation results demonstrated that the MFPA outperformed FPA in the aspect of higher accuracy, where 75.35% and 92.13% of improvements were observed in two considered case studies.
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