Abstract
In this article, the detailed description of a smartphone-based analytical method to turn a smartphone into a colorimeter is described and applied to mural painting replicas. The method consists of a camera characterization process, to estimate CIELAB values from RGB camera responses, correcting for potential experimental interferences, like the effect of the lighting/capture geometry or software for color modification and enhancement. Next, the estimated CIELAB descriptors were used to build a chemometric Support Vector Classifier to objectively distinguish among the colors of the different pigments. The method was validated in terms of color reproduction and classification performance.•A smartphone-based method is described to capture mural painting color.•A color gamut-specific camera characterization procedure is developed and the performance of the smartphone-based colorimeter is compared with a spectrophotometer.•A classification method based on the estimated CIELAB descriptors is validated in terms of classification performance.