Evaluation of plum fruit maturity by image processing techniques

Abstract

Maturity is the key factor which determines the storage life and ripening quality of fruits. In order to provide marketing flexibility and to guarantee the acceptable eating quality to the buyer it is very critical to determine the right maturity stage. Maturity indices are also important for trade regulation, marketing strategy and for the efficient use of labor and resources. The proposed system is based on implementation of image processing techniques on the JPEG images of different maturity stages of the plum variety ‘Satluj Purple’ grown under sub-tropical conditions. The external quality features like color, texture and size were analyzed. Color feature was extracted by using mean RGB values. Entropy, Local Binary Pattern and Discrete Cosine transformation were used for extracting textural features. Correlation coefficients between images of various categories were recorded to determine the most dominant factor for classification. Multi-Attribute Decision Making theory was used for taking final decision. The developed system accurately determined the maturity level. Color was found to be the most dominant factor for classifying the plums according to maturity level. The error percentage was less than 2.4%, when the length and width computed from application were compared with the manual readings. When RGB indices of fruit images were correlated with chemical properties of fruits, strong association was found between fruit acidity and mean intensity of green color (R² = 0.9966). Significant variability in total soluble solids was also explained by variation in R/G ratio (R² = 0.8464).