Single Gaussian Model as an Effective Method for Moving Target Detection

The Single Gaussian Model provides an effective technique for detecting moving targets in video sequences. This method utilizes a Gaussian distribution to model the background, enabling the identification of foreground objects in motion. In practical implementation using MATLAB, developers can leverage built-in functions such as `normpdf` for probability density calculations and array operations for efficient pixel-level processing. The algorithm typically involves initializing background parameters, updating the Gaussian model frame-by-frame using recursive equations, and applying statistical thresholds for foreground segmentation. Additionally, MATLAB's Image Processing Toolbox offers complementary functions like `imsubtract` for background subtraction and morphological operations for noise reduction. The Single Gaussian Model can also be integrated with advanced techniques such as Mixture of Gaussians (MoG) to enhance detection accuracy and computational efficiency, particularly in dynamic environments with varying lighting conditions.