Improvement of activity level detection in dynamic speckle patterns with fuzzy logic operators

NOELIA I. ECHEVERRÍA; GUZMÁN, MARCELO NICOLÁS; MARIELA AZUL GONZALES; LUCIA ISABEL PASSONI; ESTEFANY CUJANO AYALA; RAFAEL ESPIN ANDRADE

Workshop; International Virtual Workshop of Business Analytics Eureka 2019; 2019

A set of fuzzy logic operators are evaluated to detect activity level in dynamic speckle patterns. An experiment of drying level in painted samples is used. The drying process generates a surface activity due to the evaporation of the solvents that decreases as the sample dries.Painted samples with different drying levels are illuminated with a laser beam. Due to the characteristics of the surface roughness, images sequences of speckle patterns (dynamic laser speckle, SLD) are obtained. These SLD se-quences are analyzed with signal processing techniques in time and frequency domain, which generates spatial patterns (images) that show the level of sample activity. Nevertheless, the discrimination level among different drying stages is considered rather insufficient. To improve the level of discrimination, different fuzzy logic operators are applied and compared.A substantial improvement in the separability and subsequent detection of the sample drying level is obtained, evidencing the utility of fuzzy logic opera-tors in the design of a decision support system.