X‐ray Micro‐CT: How Soil Pore Space Description Can Be Altered by Image Processing
The analyses were based on five performance indicators: misclassification error, non‐region uniformity, and relative errors in porosity, conductance, and pore shape. Three levels of pre‐segmentation noise reduction were tested, as well as two levels of post‐segmentation noise reduction. Three segmen...
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| Định dạng: | BB |
| Ngôn ngữ: | English |
| Thông tin xuất bản: |
2020
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| Truy cập trực tuyến: | http://tailieuso.tlu.edu.vn/handle/DHTL/9681 |
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| Tóm tắt: | The analyses were based on five performance indicators: misclassification error, non‐region uniformity, and relative errors in porosity, conductance, and pore shape. Three levels of pre‐segmentation noise reduction were tested, as well as two levels of post‐segmentation noise reduction. Three segmentation methods were tested (two global and one local). For the local method, the threshold intervals were selected from two concepts: one based on the histogram shape and the other on the image visible‐porosity value. The results indicate that pre‐segmentation noise reduction significantly (p < 0.05) improves segmentation quality, but post‐segmentation noise reduction is detrimental. The results also suggest that global and local methods perform in a similar way when noise reduction is applied. The local method, however, depends on the choice of threshold interval. |
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