Defect Discrimination of Mango Using Image Processing Techniques

Abstract

Defect discrimination is a crucial factor in evaluating the quality of mango. The flaw mark on the flesh remark about the defunctness of mango fruit. The internal defect of mango fruit is often directly proportionate to the area of flaw marks on the skin. The defect discrimination of mango fruit manually with respect to the area of flaw marks is challenging, erroneous, and time-consuming. Hence, the development of automated techniques for defect discrimination of mango fruit is needed. Here, an image processing method is developed to discriminate the defective flaw mark on the skin of mango fruit into three categories, i.e., good, average, and bad. The experimentation reveals that the proposed method successfully categorizes the mango as per the area of flaw marks on the mango fruit’s skin.