Screening analysis of seston from a domestic wastewater treatment plant using digital images

Abstract

This paper concerns the use of digital images of seston to monitor different ponds of a domestic wastewater treatment plant. For this purpose, a commercial camera was employed to photograph the seston samples and an automatic procedure based on the Hough Circle Transform was used to segment the resulting picture. Multivariate techniques were then employed to analyze the seston images in terms of their RGB colour components. The results indicate that such colour components undergo a significant change after each stage of the wastewater treatment process, according to a Hotelling T² test (p-value smaller than 10⁻⁴). This finding was corroborated by the use of quadratic discriminant analysis (QDA), which resulted in the correct classification of all samples according to the treatment stage. In addition, it was found that differences in the illumination of the samples can be standardized by converting the RGB data to the YCbCr format and correcting the luminance (Y) component. This correction may unveil changes in the seston features that were previously masked by the illumination variability.