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A rapid method based on computer vision for the analysis of hardness and eutrophication levels in water bodies

机译：一种基于计算机视觉的快速方法，用于分析水体中的硬度和富营养化水平

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Water monitoring is essential in providing quality water to the communities which use water from nearby water bodies. In this study, a rapid method was analyzed. This method uses computer vision techniques to determine the total hardness (TH) and total phosphorus (TP) in five selective water bodies which include lakes and ponds. TH was determined by a color complex method using Eriochrome Black T indicator and TP was determined by another color-based method using a molybdate acid mixed reagent. These experiments were carried out in microwell plates of volume 5 mL. Images of the plate were acquired and regions of interests (ROIs) were obtained using suitable software and further subjected to image processing techniques to get their gray intensity values and RGB intensity values. These values were further fitted in to various linear regression models to derive equations for calculation of TH and TP concentrations. ROIs from sample water test images were analyzed in the same method to calculate TH and TP values which were further validated using standard testing methods. Results show that two out of three prescribed methods had a high precision with standard methods. Out of five samples tested, four samples showed that the water bodies have TP values in the range of 30-100 mu g/L which is eutrophic in nature. One sample, a temple pond, exhibited a whopping 119 mu g/L of TP which is considered as hypereutrophic. TH value of this sample was 227 mg/L which is considered as high hardness. Computer vision-based color processing method proved to be the best method for the rapid analysis of water quality parameters in situ.
机译：水监控对于向使用附近水体的水的社区提供优质水至关重要。在这项研究中，分析了一种快速方法。该方法使用计算机视觉技术确定五个选择性水体（包括湖泊和池塘）中的总硬度（TH）和总磷（TP）。 TH是使用Eriochrome Black T指示剂通过颜色络合物方法测定的，而TP是使用钼酸混合试剂通过另一种基于颜色的方法测定的。这些实验在体积为5 mL的微孔板中进行。使用适当的软件获取板的图像并获得感兴趣区域（ROI），然后对其进行图像处理技术以获取其灰度强度值和RGB强度值。将这些值进一步拟合到各种线性回归模型中，可以得出用于计算TH和TP浓度的方程式。用相同的方法分析样品水测试图像的ROI，以计算TH和TP值，并使用标准测试方法进一步验证。结果表明，三种规定方法中有两种具有标准方法的高精度。在五个测试样本中，四个样本显示水体的TP值在30-100μg / L的范围内，这是自然富营养化的。一个样品，一个寺庙池塘，表现出高达119微克/升的TP，被认为是富营养化的。该样品的TH值为227 mg / L，被认为是高硬度的。事实证明，基于计算机视觉的颜色处理方法是快速分析水质参数的最佳方法。

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