Reflectance Parameter Estimation and its Application to Surface Inspection

In this paper, we present a reflectance parameter estimation technique by using range and brightness and its relation, i.e. reflectance function. Because the reflectance function is quite complex and nonlinear, the parameter estimation is not straightforward. Therefore, we choose a coarse-to-fine approach to estimate the reflectance parameters. In the coarse step, the surface toughness is coarsely estimated by applying the partial linear method to the simplified Torrance-Sparrow reflectance model. Then the genetic algorithm is applied to the Wolff's reflectance model for more accurate estimation. In order to extend the dynamic range of CCD of laser finder, in this paper, we introduce the pseudo-brightness. The proposed reflectance parameter estimation algorithm is tested on the synthesized and real data. The results show that the estimated parameter using the synthesized data is very accurate. We also apply the proposed algorithm to inspect the flaws on shiny surfaces, which would be a promising method to discriminate between a wide range of surfaces.