A new two-step classification scheme based on nonparametric estimation of density function and scale-space filtering is presented in this paper. This scheme is able to combine traditional supervised classification techniques with clustering. After nonparametric estimation of the underlying density function, this scheme utilizes scale-space filtering and a novel classification algorithm to extract the intrinsic basic structure of the data. Then, depending on applications, one of the traditional clustering or classification techniques may be employed to obtain a final high level data structure.