Iterative region based Otsu thresholding of bright-field microscopic images of activated sludge

• Published in: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES) pp. 533 - 538
• Main Authors: Khan, Muhammad Burhan, Nisar, Humaira, Aun, Ng Choon, Lo, Po Kim
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016
• Subjects: Accuracy; activated sludge; Histograms; image processing; Image segmentation; Iterative algorithms; Lighting; Measurement; Microscopy; Noise; Otsu thresholding; segmentation assessmen; Software algorithms; Thresholding (Imaging)
• DOI: 10.1109/IECBES.2016.7843507

Image processing and analysis is a potential alternative monitoring tool for biodegradation in activated sludge wastewater treatment process. Accuracy of image analysis based predictive models depends on the quality of the segmentation of the microbial aggregates in microscopic images of activated sludge. The segmentation of the images is hindered by irregular illumination and properties of the microbial aggregates such as varying opaqueness and size. In this paper, an iterative region based Otsu thresholding is proposed for the bright field microscopic images of activated sludge. The suggested approach takes not only the statistics of grayscale intensities into account but also the regional distribution of the illumination noise. The proposed algorithm is compared with state-of-the-art Otsu, iterative Otsu and local Otsu segmentation techniques. The performance of the algorithms is assessed using accuracy, Rand index (RI) and variation of information (VI). The proposed algorithm exhibited better performance in terms of all the metrics with accuracy 0.9854, RI 0.9721 and VI 0.2141.