Moving object detection and recognition based on the frame difference algorithm and moment invariant features

In order to the complicated background of video monitoring system, a method of moving object detection and recognition was proposed based-on the frame difference algorithm and moment invariant features. In this moving object detection algorithm, data analysis was done for defined pixel region firstly, then the moving signal was produced by the frame data difference, and the moving object was captured from natural scene image sequences. In object recognition algorithm, moment invariant features were extracted from moving object region firstly, and vector standardization was done for these moment invariant features, then wavelet neural network with genetic algorithm was used as pattern recognition and automatic recognition was realized for moving object. In order to demonstrate above-mentioned method and the generalization ability of network model, simulation was done for this model in Matlab 7.0. Simulation results show that the proposed approach is a fast and effective method for moving object detection and recognition.