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Fractal Dimension Based Color Texture Analysis for Mangosteen Ripeness Grading

机译:基于分形维的山竹成熟度颜色纹理分析

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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.
机译:山竹果是泰国具有巨大出口潜力的水果之一。但是,它包含许多不良的外部和内部条件,这些条件会导致拒绝发货并降低出口的可靠性。因此,本文首次基于分形维数(FD)方法,基于光泽度(GS),中等粗糙度三类,利用外部果皮纹理分析的时空特性提出了山竹成熟度分级的方法。 (MR)和极端粗糙(ER)。在这项研究中,首次使用基于FD的特征和高斯混合模型(GMM)分类器提取了成熟的五个阶段。所得结果表明,与经典纹理特征相比,该方法可以实现更好的结果,即GS,MR和ER类的平均准确率分别为88.0%,82.0%和90.0%。

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