Ang Raymond Bing Quan, Nisar Humaira, Khan Muhammad Burhan, Tsai Chi-Yi
Department of Electronic Engineering, Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Jalan Universiti, Bandar Barat, Kampar, Perak, Malaysia.
Department of Electrical Engineering, National University of Computer and Emerging Sciences, Shah Latif Town 75030, National Highway (N-5), Karachi, Pakistan.
Microscopy (Oxf). 2019 Apr 1;68(2):144-158. doi: 10.1093/jmicro/dfy134.
Activated sludge (AS) is a biological treatment process that is employed in wastewater treatment plants. Filamentous bacteria in AS plays an important role in the settling ability of the sludge. Proper settling of the sludge is essential for normal functionality of the wastewater plants, where filamentous bulking is always a persistent problem preventing sludge from settling. The performance of AS plants is conventionally monitored by physico-chemical procedures. An alternative way of monitoring the AS in wastewater treatment process is to use image processing and analysis. Good performance of the image segmentation algorithms is important to quantify flocs and filaments in AS. In this article, an algorithm is proposed to perform segmentation of filaments in the phase contrast images using phase stretch transform. Different values of strength (S) and warp (W) are tested to obtain optimum segmentation results and decrease the halo and shade-off artefacts encountered in phase contrast microscopy. The performance of the algorithm is assessed using DICE coefficient, accuracy, false positive rate (FPR), false negative rate (FNR) and Rand index (RI). Sixty-one gold approximations of ground truth images were manually prepared to assess the segmentation results. Thirty-two of them were acquired at 10× magnification and 29 of them were acquired at 20× magnification. The proposed algorithm exhibits better segmentation performance with an average DICE coefficient equal to 52.25%, accuracy 99.74%, FNR 41.8% and FPR 0.14% and RI 99.49%, based on 61 images.
活性污泥法是污水处理厂采用的一种生物处理工艺。活性污泥中的丝状菌对污泥的沉降能力起着重要作用。污泥的正常沉降对于污水处理厂的正常运行至关重要，而丝状菌膨胀始终是阻碍污泥沉降的一个长期问题。传统上，活性污泥法处理厂的运行情况是通过物理化学方法进行监测的。另一种监测污水处理过程中活性污泥的方法是使用图像处理和分析技术。良好的图像分割算法性能对于量化活性污泥中的絮凝体和丝状菌很重要。在本文中，提出了一种使用相位拉伸变换对相差图像中的丝状菌进行分割的算法。测试了不同强度（S）和扭曲（W）值，以获得最佳分割结果，并减少相差显微镜中遇到的光晕和阴影伪像。使用DICE系数、准确率、误报率（FPR）、漏报率（FNR）和兰德指数（RI）评估该算法的性能。手动准备了61张与真实图像的金标准近似图像来评估分割结果。其中32张在10倍放大倍数下采集，29张在20倍放大倍数下采集。基于61张图像，所提出的算法表现出更好的分割性能，平均DICE系数为52.25%，准确率为99.74%，FNR为41.8%，FPR为0.14%，RI为99.49%。
