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Automated Internal Classification of Beadless Chinese ZhuJi Fleshwater Pearls based on Optical Coherence Tomography Images

View Article: PubMed Central - PubMed

ABSTRACT

Optical coherence tomography (OCT) has been applied to inspect the internal defect of beadless Chinese ZhuJi fleshwater pearls. A novel fully automated algorithm is proposed to classify between normal and defective sub-layer in nacre layer. Our algorithm utilizes the graph segmentation approach to estimate the up and down boundaries of defect sub-layers from flattened and cropped image, and also proposes the strategy for edge and weight construction in segmentation process. The vertical gradients of boundary pixels are used to make grading decision. The algorithm is tested by typical pearl samples, and achieves 100% classification accuracy. The experiment result shows the feasibility and adaptability of the proposed approach, and proves that the OCT technique combined with proposed algorithm is a potential tool for fast and non-destructive diagnosis of internal structure of beadless pearl.

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The generalized algorithm schematic.
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f3: The generalized algorithm schematic.

Mentions: After acquiring the OCT images of pearls, the task of classification algorithm was to detect the calcite layer and make the classification decision. The feature of the calcite sub-layer was interference intensity increasing, which was larger than that of normal nacre sub-layer and presented lighter area in image. Hence, the main step of algorithm was shifted to identify the calcite layer. The core steps of proposed algorithm are described in Fig. 3.


Automated Internal Classification of Beadless Chinese ZhuJi Fleshwater Pearls based on Optical Coherence Tomography Images
The generalized algorithm schematic.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036028&req=5

f3: The generalized algorithm schematic.
Mentions: After acquiring the OCT images of pearls, the task of classification algorithm was to detect the calcite layer and make the classification decision. The feature of the calcite sub-layer was interference intensity increasing, which was larger than that of normal nacre sub-layer and presented lighter area in image. Hence, the main step of algorithm was shifted to identify the calcite layer. The core steps of proposed algorithm are described in Fig. 3.

View Article: PubMed Central - PubMed

ABSTRACT

Optical coherence tomography (OCT) has been applied to inspect the internal defect of beadless Chinese ZhuJi fleshwater pearls. A novel fully automated algorithm is proposed to classify between normal and defective sub-layer in nacre layer. Our algorithm utilizes the graph segmentation approach to estimate the up and down boundaries of defect sub-layers from flattened and cropped image, and also proposes the strategy for edge and weight construction in segmentation process. The vertical gradients of boundary pixels are used to make grading decision. The algorithm is tested by typical pearl samples, and achieves 100% classification accuracy. The experiment result shows the feasibility and adaptability of the proposed approach, and proves that the OCT technique combined with proposed algorithm is a potential tool for fast and non-destructive diagnosis of internal structure of beadless pearl.

No MeSH data available.