Machine Vision Based Techniques for Automatic Mango Fruit Sorting and Grading Based on Maturity Level and Size

Abstract

In recent years automatic vision based technology has become more potential and more important to many areas including agricultural fields and food industry. An automatic electronic vision based system for sorting and grading of fruit like Mango (Mangifera indica L.) based on their maturity level and size is discussed here. The application of automatic vision based system, aimed to replace manual based technique for sorting and grading of fruit as the manual inspection poses problems in maintaining consistency in grading and uniformity in sorting. To speed up the process as well as maintain the consistency, uniformity and accuracy, a prototype electronic vision based automatic mango sorting and grading system using fuzzy logic is discussed. The automated system collects video image from the CCD camera placed on the top of a conveyer belt carrying mangoes, then it process the images in order to collect several relevant features which are sensitive to the maturity level and size of the mango. Gaussian Mixture Model (GMM) is used to estimate the parameters of the individual classes for prediction of maturity. Size of the mango is calculated from the binary image of the fruit. Finally the fuzzy logic techniques is used for automatic sorting and grading of mango fruit.