Computer vision and machine learning analysis of commercial rice grains: A potential digital approach for consumer perception studies

Abstract

Rice quality assessment is essential for meeting high-quality standards and consumer de-mands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morpho-metric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Fur-thermore, the ANN models were deployed and eva..