Machine vision based tomato grading and classification

Abstract

Agriculture is one of the major sources in developing the economy of newlineany country across the world. Based on the growth of world s population year by newlineyear, the necessity of the agricultural product has also increased to supply quality newlinefood to the human. Among the different agricultural products, tomatoes are a newlinesignificant and famous fruit crops. Tomatoes offer numerous basic and beneficial newlinesupplements to people for example, they contain cancer-preventing agents and newlinenutrients C and A. To increase the productivity of tomatoes and to meet the newlinestandard of supply in the market, numerous fruit grading systems have been newlinedeveloped in recent years. Detection of diseases in tomato is very useful in newlineyielding high harvest. Usually, the traditional way of identification of diseases and newlinematurity levels of fruits is not accurate, since it is based on human eye assessment newlineand centred on the human expertise. Therefore, to improve the accuracy in newlinedetecting the quality of fruits, different artificial techniques have been suggested newlineby different investigators. newline