Prediction of nanosilver and dye content on silk fabric using a scanner-based artificial intelligence technique

Abstract

Purpose

This paper aims to investigate using scanner-based adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs) and polynomial regression methods for prediction of silver nanoparticles (AgNPs) and dye concentrations on AgNP-treated silk fabrics.

Design/methodology/approach

For estimation of the dye and AgNPs concentration using image processing, the silk fabrics were scanned under the condition of 200 pixels per inch. The red green blue (RGB) values of scanned images were obtained after applying the median filter. Then, the relationship between scanner RGB values and dye and AgNPs concentrations were obtained by using artificial intelligence methods such as ANFIS and ANNs.

Findings

The best result was achieved by the ANFIS system for calculation concentration of dye with 0.07% error and concentration of AgNPs with 0.008 (gr/l) error. The obtained results indicate that the performance of the ANFIS system method is better than the other methods.

Originality/value

Using a scanner-based artificial intelligence technique for prediction of nanosilver and dye content on silk fabric.

Citation

Shams Nateri, A., Hasanlou, E. and Hajipour, A. (2022), "Prediction of nanosilver and dye content on silk fabric using a scanner-based artificial intelligence technique", Pigment & Resin Technology, Vol. 51 No. 3, pp. 372-380. https://doi.org/10.1108/PRT-02-2021-0023