Defect Detection in Fruit and Vegetables by Using Machine Vision Systems and Image Processing

Abstract

Today in the agricultural industry, many defects affect production efficiency; this paper aims to show how the combination of machine vision (MV) and image processing (IP) helps to detect the defective areas of products. Defects generally appear due to insect damage, scarring, product decay, and so on. In this review, the importance of quality inspection in the agricultural industry and its effect on worldwide markets are highlighted and the ways which help to categorize the products by their defections. In the first step, as long as agricultural products are harvested, in a suitable condition with good illumination, they are photographed by special cameras and evaluated by the IP science. In the next step, they can be classified based on the detected defection. Many classification algorithms allow us to categorize products based on the quality and type of their defects. Using a combination of MV and IP, followed by the use of special classification algorithms, helps to have more efficiency in the detection of defects in harvested products.