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A moving target detection algorithm based on GMM and improved Otsu method

Based on Gaussian mixture model, an improved detection algorithm, which aimed at updating the real-time character and accuracy of the moving target detection in intelligent video surveillance systems effectively, is elaborated in this paper. It combines the advantages of GMM and improved maximum between class variance method. The algorithm not only improves the speed of detecting targets in the intelligent systems, but also solves the inherent problems efficiently in poor real-time performance and error detection problem. In conclusion, the experiment results demonstrated that the algorithm has an excellent adaptability and anti-interference performance to fit the complicated situation and changing environment.