Automatic detection of mango ripening stages - An application of information technology to botany

Maturity is the most important factor to determine the storage-life and quality of fruits like mangoes. Fruit maturity can be recognized by different attributes and among them skin color is the most significant criteria for judging maturity. Typically, human experts visually detect the fruit color to identify the maturity stages which is very prone to error. In this paper, a method of digital image processing has been proposed to classify mangoes into six maturity stages according to the United States department of agriculture (USDA) standard classification. The experimentation considers sample images of more than 100 mangoes of different stages. A total of 24 image features are extracted and then correlation based and information gain based evaluation has been performed in order to select the most informative feature sets. Categorization is done using the decision tree which provides up to 96% classification accuracy.