Empirical mode decomposition descriptor for plane closed curves

Empirical mode decomposition (EMD) developed by Huang et al. is a nonlinear data analysis method for nonstationary real-valued time series. It has been applied extensively in many research areas. Recently, several generalized EMD methods for complex-valued data analysis was proposed. Since a plane closed curve comprises many two-dimensional (2D) space data points, one can imagine that the boundary points of a plane closed curve as a complex data sequence in the complex plane, and make use of the newly developed complex EMD (CEMD) to do further analysis. We have found that we can use CEMD to achieve boundary points noise-reduction of plane closed curves and perform shift-invariant, scale-invariant and rotation-invariant pattern recognition.