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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Food & Water Marine & Wildlife Sign in to save

Automatic Counting and Classification of Microplastic Particles

2018 25 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Javier Lorenzo-Navarro, Javier Lorenzo-Navarro, May Gómez, Alicia Herrera Alicia Herrera May Gómez, May Gómez, Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Javier Lorenzo-Navarro, Javier Lorenzo-Navarro, Javier Lorenzo-Navarro, Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera Modesto Castrillón-Santana, Modesto Castrillón-Santana, Modesto Castrillón-Santana, Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera May Gómez, Alicia Herrera Modesto Castrillón-Santana, Javier Lorenzo-Navarro, May Gómez, May Gómez, Alicia Herrera May Gómez, May Gómez, May Gómez, Alicia Herrera May Gómez, Modesto Castrillón-Santana, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera Modesto Castrillón-Santana, May Gómez, Pedro A. Marín-Reyes, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera Alicia Herrera Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera May Gómez, Alicia Herrera Alicia Herrera May Gómez, Alicia Herrera May Gómez, Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera Alicia Herrera May Gómez, May Gómez, Alicia Herrera May Gómez, May Gómez, Alicia Herrera Alicia Herrera May Gómez, May Gómez, May Gómez, May Gómez, Alicia Herrera

Summary

Researchers developed an automatic system for counting and classifying microplastic particles in marine samples, applying image analysis techniques to address the growing problem of plastic debris entering the food chain via marine species ingestion.

Microplastic particles have become an important ecological problem due to the huge amount of plastics debris that ends up in the sea. An additional impact is the ingestion of microplastics by marine species, and thus microplastics enter into the food chain with unpredictable effects on humans. In addition to the exploration of their presence in fishes, researchers are studying the presence of microplastics in coastal areas. The workload is therefore time consuming, due to the need to carry out regular campaigns to quantify their presence in the samples. So, in this work a method for automatic counting and classifying microplastic particles is presented. To the best of our knowledge, this is the first proposal to address this challenging problem. The method makes use of Computer Vision techniques for analyzing the acquired images of the samples; and Machine Learning techniques to develop accurate classifiers of the different types of microplastic particles that are considered. The obtained results show that making use of color based and shape based features along with a Random Forest classifier, an accuracy of 96.6% is achieved recognizing four types of particles: pellets, fragments, tar and line.

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