In this paper we focus on the pointwise Lipschitz regularity in 1D and 2D. We put the emphasis on its invariance properties to a wide range of transformations. Wavelets algorithms provide fast computations, which is desirable in the applications. In addition to theoretical properties, a practical evaluation of its robustness is possible in practice. This leads to the conclusion that the regularity stands out as a robust pointwise features in 1D as well as in 2D. As an application, we use it to extract features that are indicators of potential fraud, through the processing of trade data.
Keywords: Lipschitz regularity, wavelets, feature extractionJRC.G.2-Global security and crisis managemen
