Publication: Fractal Dimension Based Color Texture Analysis for Mangosteen Ripeness Grading
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Issued Date
2019
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85081086532
Rights Holder(s)
Scopus
Bibliographic Citation
Proceedings - 2019 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2019
Suggested Citation
Phothisonothai M., Tantisatirapong S. Fractal Dimension Based Color Texture Analysis for Mangosteen Ripeness Grading. Proceedings - 2019 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2019. doi:10.1109/ISPACS48206.2019.8986398 Retrieved from: https://hdl.handle.net/20.500.14740/5037
Author(s)
Abstract
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. © 2019 IEEE.