Laboratory, Field and In-Situ Soil Characterization Through Image Processing

土壤分类是岩土、土工环境和岩土地震工程场地表征的首要任务。粒度分布的评估是分类的关键。尽管存在显著的缺点，粒度分析普遍是通过筛和比重计测试进行的。因此，正在进行一项研究方案，开发硬件、分析工具和软件，以便从实验室收集的谷物组合图像中确定土壤的特征；地上的：在地上的田野；从地表以下。这项工作可能会带来更清洁、更快、更高效、成本更低、更准确的粒度测定和地层圈定。早期的图像处理工作成功地确定了当颗粒尺寸相对均匀时的主要颗粒尺寸，或者如果颗粒可以在图像捕获之前通过尺寸快速分离。当土壤包含一系列粒度时，从图像中评估粒度分布变得更加复杂。先前使用图像纹理特征和小波数学的技术为边缘像素密度（EPD）、边缘段大小（ESS）和数学形态学等新方法铺平了道路，这些新方法将产生更复杂的粒度分布。较新的技术可能需要在一定范围的放大倍率下捕获图像。对于实验室，正在开发一种系统，用于使用沉淀柱按大小快速分离土壤样品。这允许分段图像收集和传统粒度分布曲线的组合。硬件和图像采集系统的设计是为了方便尺寸识别至0.005毫米直径，通常引用的尺寸阈值为？和克莱?。硬件开发将作为跨学科本科设计项目的一部分进行，学生来自多个学科，包括土木/岩土工程、机械设计、图像处理和数理统计。在现场应用方面，该研究将开发一个快速响应系统，以确定地表土壤的粒度分布，使用两种不同的方法：数学形态学和边缘检测，以确定边缘像素密度（EPD）和边缘段大小（ESS）。初步证据表明，这些方法应用于在多个尺度上拍摄的图像，可以提供甚至分级良好的土壤的粒度分布，而不需要颗粒分离。该研究还将开发一种可快速部署的野外便携式计算机和摄像系统。对于亚表面粒度评估，将使用视觉锥穿透仪（viscone penetration meter，简称vispt）进行图像采集。早期的研究表明，质地指数只能探测地层的变化，而粒度的测定一直是一个过于复杂的问题。采用新提出的图像处理方法，使原位粒度测定变得容易。vispt数据将在印第安纳州西南部一个特征非常明显的砂石采石场收集。现有的可用数据包括连续土壤采样和20米深度的粒度分布。冰川冲刷遗址包括大量的土壤层次，从沙质砾石到粘土粉砂。本文开发的用于土壤粒度表征的成像方法可直接应用于其他学科和行业，在这些学科和行业中，各种尺度的制造部件，制剂成分，自然发生的生物或地质物质的尺寸，以及通过图像处理对遥感物体的解释对于质量控制，检查，诊断，状态评估和未来行为的预测至关重要。这些行业包括制药、食品加工、材料科学、粉末冶金、微生物学等。

Soil classification is the first and foremost task of geotechnical, geoenvironmental and geotechnical earthquake engineering site characterization. Assessment of grain size distribution is essential to the classification. Despite significant shortcomings, grain size analysis is ubiquitously performed by sieve and hydrometer tests. A research program is therefore being undertaken to develop the hardware, analytical tools and software for characterization of soils from images of grain assemblies collected in the laboratory; above ground in the field; and from below the ground surface. The effort may result in cleaner, quicker, more efficient, less costly and more accurate grain size determination and stratigraphic delineation. Earlier image processing efforts were successful at determining the dominant grain size when particles are relatively uniform in size, or if the particles can be quickly segregated by size prior to image capture. The assessment of grain size distribution from images becomes orders of magnitude more complex when a soil contains a range of grain sizes. Previous techniques using image textural features and wavelet mathematics have paved the way for new methods including edge pixel density (EPD), edge segment size (ESS) and mathematical morphology that will yield more complex grain size distributions. The newer techniques may necessitate image capture at a range of magnifications.For the laboratory, a system is being developed for rapidly segregating a soil specimen by size using a sedimentation column. This permits piecewise image collection and assemblage of a traditional grain size distribution curve. The hardware and image collection system is being designed to facilitate size recognition down to 0.005 mm diameter, the commonly cited size threshold between ?silt? and ?clay?. The hardware development will be performed as part of an interdisciplinary undergraduate design project with students from several disciplines including civil/geotechnical engineering, mechanical design, image processing and mathematical statistics.For field applications, the research will develop a rapid response system to determine the grain size distribution of soils at the ground surface using two different approaches: mathematical morphology and edge detection to determine edge pixel density (EPD) and edge segment size (ESS). Preliminary evidence suggests these methods applied to images taken at multiple scales may provide the grain size distribution of even well-graded soils without the need for particle segregation. The research will also develop a rapidly deployable field portable computer and camera system. For subsurface grain size assessment, the vision cone penetrometer (VisCPT) will be used for image collection. Earlier studies have shown that textural indices can only detect changes in stratigraphy, but grain size determination has been too complex a problem. With the newly proposed image processing methods, in-situ grain size determination becomes tractable. VisCPT data will be collected at an exceptionally well characterized sand and gravel quarry in southwestern Indiana. Existing available date data includes continuous soil sampling and grain size distributions to a depth of 20 meters. The glacial outwash site includes a large assortment of soil gradations ranging from sandy gravels to clayey silts.The imaging methods developed herein for soil grain size characterization have direct application to other disciplines and industries where the sizing of manufactured components at various scales, ingredients in preparations, naturally occurring biologic or geologic matter, and interpretation of remotely sensed objects through image processing are essential to quality control, inspection, diagnosis, state assessment, and prediction of future behavior. Such industries include pharmaceuticals, food processing, materials science, powder metallurgy, microbiology and others.