Robust and automatic tracking method of infrared extended object based on EM-like algorithm

A robust and automatic tracking scheme fo r moving extended object in infrared video images based on expectation maximization (EM) algorithm was proposed. Firstly, local morphological Top-Hat operator was adopted to restrain the image background and eliminate the noises, and the grey level of infrared objects became more salient using the platform histogram technique. Secondly, the gray level feature template of the infrared object was built based on the Gaussian weighted histogram which included gray pixel position. Finally, the localization and shape size of infrared object in every frame were obtained with the EM algorithm, which was an iterative numerical tool for computing the parameter set of maximal likelihood function of density distribution. The experiments demonstrate that the proposed method can track infrared object with adaptive bandwidths and enhance SNR of the infrared image. It efficiently guarantees the accuracy, stability and continuity in real time tracking infrared object.