Paper Surface Characterisation by Laser Profilometry and Image Analysis

Standard air leakage-based methods give insufficient information about paper surface topography. In this study, laser profilometry was used to measure topography directly. The analysis was performed with ImageJ, an image processing package written in Java. ImageJ plug-ins were developed to assess paper surface-roughness statistics. Gaussian filtering was used to separate the waviness from the roughness and thus assess the structure at different wavelengths. Number and heights of peaks and depths of valleys were also assessed. A plug-in for detecting the local facet orientation using Sobel operators is presented and described in detail, along with the implications of local facet orientation on light scattering and gloss. Segmentation of the pores was accomplished by using a rolling sphere, giving also a new definition of the paper surface. Such objective segmentation enhances the quantification of the real surface-pore volume.