A Highly Accurate and Automated Method for Quantifying Spherical Microplastics Based on Digital Slide Scanners and Image Processing

Abstract

Microplastics (MPs), the emerging pollutants appeared in water environment, have grabbed significant attention from researchers. The quantitative method of spherical MPs is the premise and key for the study of MPs in laboratory researches. A novel method called VS120-MC for spherical MPs quantification was proposed in this work. The core strategy of this method involved the innovative usage of digital slide scanner VS120 to achieve full-area scanning of filter membranes enriched with MPs and the semi-automatic image recognition of MPs implemented by a self-developed software, MPs-Counter. The full-area scanning photography was employed to fundamentally avoid the error caused by random or partition sampling modes whose quantification results showed limited correlation with whole-membrane scanning. To accomplish high-performance batch recognition, MPs-Counter was designed on the basis of circle Hough transform (CHT), and combined with the homemade Weak-Circle Elimination Algorithm (WEA) which could eliminate the false-positive overlapping circles. In addition, the irregular impurities were well excluded by the Variable Coefficient Threshold (VCT). Finally, lower than 0.6% and 3% recognition error rate of simulated and real MPs images could be achieved by MPs-Counter with fast processing speed (about 2 s/image). It was also found that MPs-Counter exhibited significantly greater resilience to factors such as aggregated indices, overlapping configurations of MPs, and varying image resolutions when compared to Image-Pro Plus, an open-source software. Overall, VS120-MC eliminated the error caused by traditional photography and realized an accurate, efficient, stable image processing tool, providing a reliable alternative for the quantification of spherical MP.

Keywords: Spherical microplastics quantification, Digital slide scanners, Image processing, Circular Hough transform