Wavelet strategy for surface roughness analysis and characterisation Original Research Article

This paper proposes a new strategy for surface roughness analysis and characterisation based on wavelets. A three-step algorithm is proposed to perform a task of surface roughness discrimination between surface texture images coming from eight different engineering processes. The first step of the algorithm is the analysis of the images by frequency normalised wavelet transform (FNWT). From this process, images are obtained that are a space-frequency representation of the surface textures. Next, simple characterisation parameters are extracted from these images. Finally, two discrimination processes are presented, namely discriminant analysis and cluster analysis. It is seen that this strategy gives excellent results for this task which justifies its use for practical industrial applications.