Visual objects tracking and identification based on reduced quaternion wavelet transform

In this paper, a new method for tracking moving objects based on reduced quaternion wavelet transform by using color space information is proposed. The reduced quaternion wavelet transform is a new multi-scale analysis tool for geometric image features. Meanwhile, it is a near-shift-invariant tight frame representation whose coefficients can sport local image shift and geometric information. The main objective of visual tracking is to closely follow objects in each frame of video stream. The new proposed method can calculate the mean value and edge energy of visual objects by using the reduced quaternion wavelet coefficients. The experimental results show that the proposed method is effective and efficient.