1132 Muhammad Burhan Khan et al.
was fed by the influent of a municipal AS plant. The PCM images were acquired by observing the samples collected from aeration tanks of the plants, using an Olympus BX43 micro- scope. The microscope was equipped with a DP26 CCD camera that was interfaced to a computer using IEEE1394b cable connection. The images were acquired using Olympus CellSensDimension software. The image acquisition setupwas assembled and manufactured byOlympus, Tokyo, Japan. 12 µl volumes of the samples were placed on a slide with a coverslip 18×18mmin size. For the image acquisition, the coverslip was scanned along a cross-centered on the coverslip. The images were acquired at 10× or 20× magnification with their number depending on the size and number of flocs and filaments. Higher magnification was used for small filaments and vice versa. The size of each image was 1,224×960 pixels with the pixel size 0.7015 µm at 10× and 0.3481 µmat 20×magnifi-
cation.All the segmentation algorithms, reported in this paper, have been implemented and assessed using the software packageMATLAB (Mathworks, Natick,MA, USA).
Segmentation Algorithms
The following algorithms are proposed for segmentation of PCM images of AS samples.
Saturation-Based Segmentation In the literature, red-green-blue (RGB) color space has been used in the context ofAS images (Mesquita et al., 2013; Khan et al., 2015a, 2015b). We observed that the S channel of the HSV (hue, saturation, and value) representation has better contrast from the perspective of filaments, as shown in
Figure 3. It also minimizes the halo artifacts around the filaments. Therefore, we used the saturation channel of the HSV format of the phase-contrast image for segmentation. Subsequently, Otsu (1979) thresholding was employed to segment the flocs and filaments. Otsu thresholding alone fails to segment the filaments, and the flocs are over- segmented in case of RGB image. Our algorithms improve the results by employing the S channel grayscale image.
Figure 3. a: Original red-green-blue image, (b) R channel, (c) G channel, (d) B channel, (e) H channel, (f) S channel, (g) V channel.
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