Texture Evaluation of Automotive Coatings by Means of a Gonio-Hyperspectral Imaging System Based on Light-Emitting Diodes
Source abstract
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.
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Research context
OpenAlex topics: Color Science and Applications · Industrial Vision Systems and Defect Detection · Textile materials and evaluations
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Centre for Sensors, Instruments and Systems Development, Universitat Politècnica de Catalunya, Rambla de Sant Nebridi 10, 08222 Terrassa, Spain
Department of Optics, Pharmacology and Anatomy, University of Alicante, San Vicente del Raspeig Road, 03690 San Vicente del Raspeig, Spain
Global Innovation Center, Axalta Coating Systems, 1050 Constitution Avenue, Philadelphia, PA 19112, USA
Funding
Ministerio de Ciencia e Innovación · Ministerio de Economía y Competitividad
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