Thermal imaging with fuzzy classifier for maturity and size based non-destructive mango (Mangifera Indica L.) grading

This is the era of ICT technologies. As it's an important task to reach consumer's demand for good quality mango, automation in grading of mango (Mangifera Indica L.) is required. This paper is addressing the grading issue of agricultural produce based on its maturity and size. The Fuzzy inference system is used for decision-making process. Prediction of mango's maturity is done through its skin's color but for some exceptional tribe of mango like “Langdo”, skin color will remain the same for its lifetime. In such cases, normal imaging (reflective imaging) will not work for predicting its maturity. One can use infrared, x-ray or thermal imaging for maturity prediction. Here mango grading is performed based on maturity and size feature. For that, with mean intensity algorithm in L*a*b* color space and FLIR ONE thermal camera is used to predict the maturity of mango. Size of mangois predicted by three parameters namely weight, eccentricity and area. Fuzzy classifier is used for predicting size feature. To grade mango decision making theory is used and mango is graded in two different classes. Time needed to grade a mango is 2.3 seconds and accuracy received is 89%.