AI approach to asses perceived blackness

The study investigates how the amount of matting agent affects the appearance and perceived blackness of polyurethane (PU) black panels. To do so, various neural network models were used to model visual perception based on colorimetric and geometric properties. As the researchers reclaim, their study is the first to use AI to model and predict perceived blackness based on appearance attributes, providing a comprehensive understanding of the effects of matting agents and streamlining the evaluation process.

Conserving both time and resources

The research is intended to simplify the evaluation process of blackness in industrial settings, reducing the need for labour-intensive visual assessments. According to the reseachers, it effectively eliminates the need for time-consuming visual assessment experiments traditionally used for blackness evaluations in industrial settings and greatly simplifies the evaluation process, conserving both time and resources while maintaining reliable and precise assessments.

The study has been published in Progress in Organic Coatings, Volume 199, February 2025, 108963.

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