A Machine Vision Approach for Grading of Onions

B. L. Benisha Bennet

doi:10.37591/joipprp.v1i2.111

Abstract

Grading of fruits and vegetables (on the basis of various external and internal quality attributes) is an important unit operation in the food industry. For products such as onions, grading is performed mainly on the basis of size. In the present study, a machine vision system was used to grade onions into three categories (extra-large, medium and small) based on variations in size. The machine vision system consisted of a CCD camera, illumination source, holding unit, sample platform, and computer. The geometric mean diameter of the sample was used as the classification parameter. It was observed that the system gave an overall classification efficiency of 93% with better results for extra-large grade. Similar approaches can be successfully implemented for classification of other agricultural products using various grading parameters.

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