Date of Publication :7th October 2016

Abstract: In agricultural and food industry the proper grading of fruits is important to increase the profitability. In this paper, a scheme for real time mango (Mangifera Indica L.) grading technique according to their maturity level and quality attributes like size, shape, weight, surface defect has been proposed. The proposed scheme works on intelligent machine vision based techniques for grading of mangoes in four different categories, which are determined on the basis of market value. In this system video image is captured by a CCD camera placed on the top of a conveyer belt carrying mangoes, thereafter several image processing techniques are applied to collect features which are sensitive to the maturity level and quality level. For maturity prediction Support Vector Machine (SVM) based classifier has been employed and for estimation of quality from the quality attributes, Multi Attribute Decision Making (MADM) system have been adopted. Finally fuzzy incremental learning algorithm has been used for grading based on maturity and quality. The performance accuracy achieved using this proposed system for grading of mango fruit is nearly 90%. Moreover, the repeatability of the proposed system is found to be 100%.

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