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A Simple Image Analysis Algorithm For Evaluation Of Extendedfilaments Length Based On The Enhanced Digitized Image

机译:基于增强数字图像的延长丝长度评估的简单图像分析算法

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An automated image analysis procedure was developed to determine extended filaments length and floc area to evaluate settling characteristics of activated sludge. Digitized image obtained by Gram staining granted the first step of algorithm, segmentation, to be extremely clear and simple. The image analysis work could become more accurate and less time consuming one to be required only 1 minute of operation time per image. Filamentous bulking phenomenon of the biological sludge was induced in a laboratory-scale bioreactor system under an extreme operational condition, and the non-bulking and filamentous bulking sludge samples captured were examined with image analysis as well as traditional settling test. There existed a linear relationship between DSVI (Diluted Sludge Volume Index) and the extended filaments length. Similar results were also obtained with the extended filaments per floc area. The arithmetic mean extended filaments length showed an excellent linearity with the DSVI. It is believed that the image analysis algorithm developed in this study can be utilized for estimation of the extended filaments length and for evaluation of the settling characteristics of activated sludge effectively.
机译:开发了一种自动图像分析程序来确定延长的长丝长度和絮凝面积,以评估活性污泥的沉降特性。通过革兰氏染色获得的数字化图像使算法的第一步(即分割)变得非常清晰和简单。图像分析工作可以变得更加准确,并且耗时更少,而每个图像只需1分钟的操作时间。在极端操作条件下,在实验室规模的生物反应器系统中引发了生物污泥的丝状堆积现象,并通过图像分析和传统沉降测试对捕获的非散状和丝状堆积污泥样品进行了检查。稀释污泥体积指数(DSVI)和长丝长度之间存在线性关系。使用每絮状物区域的延伸长丝也获得了相似的结果。算术平均长丝长度与DSVI表现出极好的线性。可以相信,这项研究中开发的图像分析算法可用于估算长丝的长度和有效评估活性污泥的沉降特性。

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