| 基于CT扫描技术的土壤孔隙定量表达优化 |
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| 引用本文： | 赵玥,韩巧玲,赵燕东.基于CT扫描技术的土壤孔隙定量表达优化[J].农业机械学报,2017,48(10):252-259. |
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| 作者姓名： | 赵玥 韩巧玲 赵燕东 |
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| 作者单位： | 北京林业大学,北京林业大学,北京林业大学 |
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| 基金项目： | 中央高校基本科研业务费专项(BLX2015-36)和国家自然科学基金青年基金项目(41501283） |
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| 摘 要： | 现有土壤孔隙量化方法主要通过图像处理软件实现孔隙结构的辨识与分析,此类通用的图像处理软件或医学处理软件未考虑土壤内部物质的复杂多变性以及孔隙结构的细小和不规则性,从而导致孔隙分割精度低进而量化误差大,为解决这一问题,本文针对土壤CT图像的特点提出了一种孔隙量化方法。该方法主要包括图像处理和量化分析两部分:选用自适应中值滤波算法去除噪声对孔隙边缘的影响,并采用迭代最佳阈值法与Canny边缘检测算子相结合的方法,准确识别出土壤孔隙结构及轮廓线;运用数学统计方法定量研究土壤孔隙率、孔隙数目、分形维数、成圆率等几何指标,用以揭示孔隙结构的复杂性和不规则性,实现对土壤孔隙的量化分析。最后,以冻融循环作用下的土壤为应用对象验证该方法性能。结果表明,本文方法能精确地定位孔隙轮廓,有效地分割孔隙结构,而且通过多种孔隙几何指标的量化可揭示出冻融循环作用对土壤结构的影响,为孔隙几何特征和空间特征的量化表达奠定了基础。
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| 关 键 词： | 土壤断层扫描图像 孔隙结构 图像处理技术 孔隙量化 |
| 收稿时间： | 2017/1/12 0:00:00 |
Optimization of Soil Pore Quantitative Expression Based on Computed Tomography Scanning Technology |
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| ZHAO Yue,HAN Qiaoling and ZHAO Yandong.Optimization of Soil Pore Quantitative Expression Based on Computed Tomography Scanning Technology[J].Transactions of the Chinese Society of Agricultural Machinery,2017,48(10):252-259. |
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| Authors: | ZHAO Yue HAN Qiaoling and ZHAO Yandong |
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| Institution: | Beijing Forestry University,Beijing Forestry University and Beijing Forestry University |
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| Abstract: | In recent years, image processing software was wisely applied to identify and analyze pore structure. However, these softwares, such as Photoshop and Image J, did not take into account the complexity of the internal material in the soil and the irregularity of pore structure, and they caused low pore segmentation precision. In order to solve the problem, a pore quantitative method based on the characteristics of soil computed tomography (CT) image was proposed. This method mainly included image processing and quantification analysis. Firstly, the adaptive median filtering algorithm was adopted to remove the effect of image noise on the edge of pore. Then, the method of iterative optimal threshold and canny edge detection was used to identify the pore structure in the soil and the contour line of the pore. Secondly, soil pore structure had evident spatial characteristics, which included soil porosity, pore number, pore radius, spore size distribution, circularity, fractal dimension, and so on. These pore geometry indicators were calculated by using the mathematical statistics method, and they could reveal the complexity and irregularity of pore structure. These geometry indicators were useful for realizing the quantitative analysis of the soil porosity. Finally, the method was applied to the soil under freeze-thaw cycle. The results showed that the method can accurately locate the pore profile, and segment the pore structure effectively. Furthermore, the effect of freezing and thawing cycles on the soil structure was revealed by quantifying the geometrical parameters of various soil pores, thus it proved the effectiveness of the method and laied foundation for quantification of soil pore geometry and spatial characteristics. |
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| Keywords: | soil computed tomography image pore structure image processing technology quantitation of pore |
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