Shape and weight grading of mangoes using visible imaging

• Automatic grading of Harumanis mangoes by its shape and weight analysis.
• The Fourier descriptor method was developed to grade the shape of Harumanis mango.
• The cylinder method was developed to grade the weight of Harumanis mango.
• Multi-classification using Support Vector Machine and Discriminant analysis.

This paper presents the work on the use of visible imaging as a tool in grading the mangoes. A Fourier-descriptor method was applied on mango images acquired by a CCD camera, to grade the fruits by their shapes. The method was able to correctly classify 98.3% using DA and 100% using SVM. It is also possible to estimate the weight of the mangoes from their images by applying the Cylinder approximation analysis method. The scatter plot between the estimated and actual values of the weight shows high correlation, with R2 equal to 94.0%. The high prediction accuracy obtained shows that this simple formula is adequate for the prediction of fruit weight and volume (measured volume using the cylinder method). The correlation formula derived based on the collected data is determined as w = 2.256 V − 157.7 where w is estimated weight in grams and V is estimated volume. Overall result for weight grading using our proposed method yields 95% accuracy.