Computer vision-based detection of liquid levels within cylindrical tanks in wastewater treatment

• Published in: Guanʻgai paishui xuebao Vol. 44; no. 6; pp. 111 - 117
• Main Authors: MA Huanhuan, LI Yunbei, ZHANG Yuanxin, HE Yu, SHI Ningning, FAN Anrui, ZHOU Linhao, HUANG Biaobing, HONG Shuangxi, ZHANG Xiaoju
• Format: Journal Article
• Language: Chinese
• Published: Science Press 01.06.2025
• Subjects: image processing; cylinder liquid level; intelligent recognition; opencv
• ISSN: 1672-3317
• DOI: 10.13522/j.cnki.ggps.2023459

【Objective】Traditional methods for measuring specific resistance of sludge in wastewater treatment are limited by low efficiency, high errors and liquid surface oscillation. To address these issues, a computer vision-based intelligent monitoring system was developed to improves accuracy and automation of the measurements and overcome the limitations of conventional methods.【Method】A multi-modal image processing and intelligent monitoring platform was developed using OpenCV. Images of a graduated cylinder were converted to the HSV color images, followed by adaptive Region of Interest (ROI) cropping and morphological gradient operations to enhance the liquid surface edge detection. An improved bilateral filter was applied to remove the noise induced by bubbles and light reflections. The Otsu algorithm was employed for image segmentation, enabling precise recognition of liquid levels. The system was implemented using the Qt5 framework, incorporating multi-threaded video capture and dynamic compensation via a Kal