Fractal Dimension Based Color Texture Analysis for Mangosteen Ripeness Grading

Mangosteen is one of the fruits that has an enormous export potential in Thailand. However, it contains numerous undesirable external as well as internal conditions which result in the shipment rejection and decrease the reliability of the export. Therefore, in this paper for the first time, we propose the method for mangosteen ripeness grading using the spatiotemporal properties of external rind texture analysis on the basis of fractal dimension (FD) approach for three classes: i.e., Glossy (GS), Medium Rough (MR) and Extreme Rough (ER). In this study, for the first time, the five stages of ripening have been extracted using FD based feature with Gaussian Mixture Model (GMM) classifier. The obtained results showed that the proposed method can perform the better results compared with the classical texture feature, i.e., average accuracy rates of 88.0%, 82.0%, and 90.0% for GS, MR, and ER classes, respectively.