Vehicle Detection and Tracking Based on Fast Wavelet Transform and Kalman Filter

A new approach for vehicle detection is proposed in this work.First,fast wavelet transform(FWT)designed for discrete signal is proposed to extract image texture,while grey level co-occurrence matrix(GLCM)is employed to measure and analyze the extracted texture.Then,vehicles can be extracted since the vehicle sections and the shadow sections have different textures in the combined foreground image.Moreover,we put forward in this work the state and observation matrixes of Kalman filter which has been employed to track vehicles under complicated traffic scenes.Experimental results in real traffic scenes reveal that the proposed techniques are effective and efficient for vehicle detection and tracking.