Oil Reheating Analysis Using a Multispectral Image by Machine Learning

This project describes Oil reheating analysis using a multispectral image. The quality of food consumed plays a pivotal role in assuring the health of a society the reheating of oil condition is predicted using a machine learning algorithm with a multispectral image.Thereafter, another algorithm is proposed to develop a spectral-clustering-based classifier to determine the effect of reheating and reuse of coconut oil. Distinct clusters were obtained for different levels of reheated oil classes and the classification was performed with an accuracy of 0.983 on training samples. Further, the input images for the proposed algorithms were generated using in-house development.