Segmentation Approach Towards Phase-Contrast Microscopic Images of Activated Sludge to Monitor the Wastewater Treatment

Abstract

Image processing and analysis is an effective tool for monitoring and fault diagnosis of activated sludge (AS) wastewater treatment plants. The AS image comprise of flocs (microbial aggregates) and filamentous bacteria. In this paper, nine different approaches are proposed for image segmentation of phase-contrast microscopic (PCM) images of AS samples. The proposed strategies are assessed for their effectiveness from the perspective of microscopic artifacts associated with PCM. The first approach uses an algorithm that is based on the idea that different color space representation of images other than red-green-blue may have better contrast. The second uses an edge detection approach. The third strategy, employs a clustering algorithm for the segmentation and the fourth applies local adaptive thresholding. The fifth technique is based on texture-based segmentation and the sixth uses watershed algorithm. The seventh adopts a split-and-merge approach. The eighth employs Kittler's thresholding. Finally, the ninth uses a top-hat and bottom-hat filtering-based technique. The approaches are assessed, and analyzed critically with reference to the artifacts of PCM. Gold approximations of ground truth images are prepared to assess the segmentations. Overall, the edge detection-based approach exhibits the best results in terms of accuracy, and the texture-based algorithm in terms of false negative ratio. The respective scenarios are explained for suitability of edge detection and texture-based algorithms.

Alternative Soil Substrates Addition Cause Deterioration in Reclaimed Soil Macropore Networks at Eastern Mining Area, China

“…All sliced images with a resolution of 80 μm were cropped to a square with side length of 3 cm by Image J 1.51 (Wayne Rasband, National Institutes of Health, Bethesda, MD, USA) to avoid soil cracks, and 1000 sliced images were selected and then imported in Avizo 9.0.1 (VSG Inc., Burlington, MA, USA) to construct a region of interest (ROI) with size of 3 × 3 × 3 cm 3 . Before the reconstruction of 3D macropore structure, contrast enhancement, non-local mean filter and unsharp mask of pore edges were processed for the 2D sliced images, and the macropores of total 24 undisturbed soil columns were identified by two adaptive threshold segmentation methods [30], they are watershed segmentation method and top-hat segmentation method which were suitable for dividing larger pores and smaller pores, respectively (Figure 2), after the macropore threshold value was determined automatically, a reasonable threshold value was further fine-tuned continuously by visual inspection for each image [31], to ensure that the shadow part of each CT image can be recognized more accurately. After segmentation, the macropores identified by two segmentation methods were combined, and the macropore networks were reconstructed and visualized in Avizo 9.0.1.…”

A State-of-the-Art Survey for Microorganism Image Segmentation Methods and Future Potential

“…In [88], nine methods for segmentation of floc from phase contrast microscopic images of activated sludge (during monitoring of waste water treatment) are assessed. These methods are saturation color channel based approach, edge detection approach (Sobel based), k-means clustering algorithm, adaptive thresholding, texture based segmentation (Bradley adaptive thresholding), watershed algorithm, Kittler thresholding, split-merge approach and top-bottom-hat filtering based method.…”

Segmentation of Activated Sludge Filaments using Phase Contrast Images

“…In this section we will review four state of art segmentation algorithms: edge based algorithm, K-means algorithm, texture based algorithm and watershed algorithm for the segmentation of filaments from phase contrast images. The methods used for segmentation are already established methods, however we will be adapting them for segmenting filaments in phase contrast microscopy 9 , in order to get an overview of the techniques that may be suitable for this modality.…”