Mango Classification System Uses Image Processing Technology and Artificial Intelligence

Abstract

The classification of mango in Vietnam and the world is being carried out mainly by direct labor of farmers using time-consuming and less efficient observations or some non-specialized machines and results for productivity not high, high cost, sorting out different types of mangoes is relatively costly. World studies of mango classification according to color, size, volume and almost done in the laboratory but not yet applied in practice. The quality assessment of mango fruit has not been resolved. So it is necessary to study image processing techniques; collect and build a database of photos of some types of mangoes in Vietnam; studying mango quality approaches and techniques, examining mango surfaces that are deep, withered, porous, deformed mangoes, ripening on mango fruit; application of image processing technology, computer vision combined with artificial intelligence in the problem of mango classification or poor quality. The goal of the study is to create a system that can classify mangoes in terms of color, volume, size, shape and fruit density. The classification system using image processing incorporates artificial intelligence including the use of CCD cameras, C language programming, computer vision and artificial neural networks. The system uses the captured mango image, processing the split layer to determine the mass, volume and defect on the mango fruit surface. This article is about the development of an automatic mango classification system using image processing technology combining artificial intelligence to control and evaluate mango quality before packaging and exporting to the market.