Quantifying the complexity of small-scale 3D laser range data

摘要

Proper characterization of surface topography is critical for understanding a wide range of chemical and biological processes at the interface. This paper describes a method for characterizing the complexity of a surface from its depth map acquired with a laser vision sensor. The technique used to calculate fractal dimension was based on the variation method. Instead of trying to estimate the dimension around 0 however, this was done at specific scales over a range of values. We will show the impact of using local information to estimate the complexity of the surface and emphasize the problems that can be encountered when blindly trying to estimate the fractal dimension of 3D data. We conclude that linear local approximation of the object should be used to quantify its complexity, and to determine the scale at which analysis should be done. The method was applied to two samples of plasma coated titanium plates generated under differenty spraying conditions. The results show that our technique can provide a quantification scheme for standardization of the coating process and can improve the validation of manufacturing technologies.