Computer Vision based Method to Detect Milk Adulteration with Water
A rapid method based on digital image analysis and machine learning technique is proposed for the detection of milk adulteration with water. Several machine learning algorithms were compared, and SVM performed best with 89.48% of total accuracy and 95.10% precision. An increase in the classification performance was observed in extreme classes. Better quantitative determination of the added water was done using SVMR with R2 (CV) and R2 (P) of 0.65 and 0.71 respectively. The proposed technique can be used for the nondestructive determination of milk adulteration with water without the necessity of any additional reagent.
Bezuayehu Gutema Asefa*