Feature Extraction Of Music Digital Drugs Properties Based On Contourlet Transformation

Digital Drugs become one of the most dangerous phenomena which effect the civil social and goes farther to destroy it. The big problem represented by that listening to any music is legal, so that this type of music not rejected by laws. In this research an approach to extiract some main properties of Music Digital Drugs in order to extinguishing the expansion of such type of music. Feature extraction of the music signal will be done based on contourlet transform by reconstruct the music signal, which normally used by patients to go relaxation, into two dimensional array to be decomposed to its coefficients in multi levels using contorlet transformation. The morphological properties (energy, correlation and homogeneity ) of the high frequency coefficients will adopted to evaluate and study the ability to extract features that belong to that music. The three morphological properties show that the studied music signals hold some common properties which can classify them in special categories that help in future to diagnose any music broadcast online is it Music Digital Drugs or not. The practical simulated using MATLAB language.