Open AccessMicroplastic Identification via Holographic Imaging and Machine Learning
Author(s) -
Bianco Vittorio,
Memmolo Pasquale,
Carcagnì Pierluigi,
Merola Francesco,
Paturzo Melania,
Distante Cosimo,
Ferraro Pietro
Publication year - 2020
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.201900153
Subject(s) - microplastics , computer science , holography , artificial intelligence , microscale chemistry , process (computing) , hyperspectral imaging , identification (biology) , environmental science , pattern recognition (psychology) , computer vision , remote sensing , optics , geology , mathematics , physics , oceanography , mathematics education , botany , biology , operating system
Microplastics (MPs) are a major environmental concern due to their possible impact on water pollution, wildlife, and the food chain. Reliable, rapid, and high‐throughput screening of MPs from other components of a water sample after sieving and/or digestion is still a highly desirable goal to avoid cumbersome visual analysis by expert users under the optical microscope. Here, a new approach is presented that combines 3D coherent imaging with machine learning (ML) to achieve accurate and automatic detection of MPs in filtered water samples in a wide range at microscale. The water pretreatment process eliminates sediments and aggregates that fall out of the analyzed range. However, it is still necessary to clearly distinguish MPs from marine microalgae. Here, it is shown that, by defining a novel set of distinctive “holographic features,” it is possible to accurately identify MPs within the defined analysis range. The process is specifically tailored for characterizing the MPs' “holographic signatures,” thus boosting the classification performance and reaching accuracy higher than 99% in classifying thousands of items. The ML approach in conjunction with holographic coherent imaging is able to identify MPs independently from their morphology, size, and different types of plastic materials.