Computer Vision and Machine Learning Analysis of Commercial Rice Grains: A Potential Digital Approach for Consumer Perception Studies
Aimi Aznan, Claudia Gonzalez Viejo, Alexis Pang, Sigfredo Fuentes
SENSORS | MDPI | Published : 2021
Rice quality assessment is essential for meeting high-quality standards and consumer demands. 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 morphometric 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. Furthermore, the ANN models were deployed and evalua..View full abstract
The authors would like to acknowledge the support from the Digital Agriculture, Food, and Wine Group from the Faculty of Veterinary and Agricultural Sciences (FVAS), The University of Melbourne.