Texture Evaluation of Automotive Coatings by Means of a Gonio-Hyperspectral Imaging System Based on Light-Emitting Diodes

Abstract

Sparkle and graininess are textural effects that appear as intrinsic spatial features of coatings containing goniochromatic pigments, whereas others such as mottling are undesired outcomes. In this study, we present new methods for the evaluation of sparkle, graininess and mottling of automotive coatings through images acquired with a novel gonio-hyperspectral imaging system based on light-emitting diodes with extended spectral sensitivity beyond the visible range (368–1309 nm). A novel analysis of sparkle that considered the amount of sparkling spots was used. Graininess was quantified through a novel statistical descriptor based on the energy descriptor computed from the histogram. A new index was proposed for an enhanced detection of mottling based on the analysis of striping, which was better observed and quantified in the infrared range. Spectral assessments showed a strong relationship with color and spectral reflectance for graininess and mottling. In conclusion, the results showed that these new spatial and spectral methods are a suitable, alternative and potential approach for the assessment of these textural features.