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Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor
We demonstrate a methodology for non-contact classification of five different plastic types using an inexpensive direct time-of-flight (ToF) sensor, the AMS TMF8801, designed for consumer electronics. The direct ToF sensor measures the time for a brief pulse of light to return from the material with...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10051388/ https://www.ncbi.nlm.nih.gov/pubmed/36992035 http://dx.doi.org/10.3390/s23063324 |
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author | Becker, Cienna N. Koerner, Lucas J. |
author_facet | Becker, Cienna N. Koerner, Lucas J. |
author_sort | Becker, Cienna N. |
collection | PubMed |
description | We demonstrate a methodology for non-contact classification of five different plastic types using an inexpensive direct time-of-flight (ToF) sensor, the AMS TMF8801, designed for consumer electronics. The direct ToF sensor measures the time for a brief pulse of light to return from the material with the intensity change and spatial and temporal spread of the returned light conveying information on the optical properties of the material. We use measured ToF histogram data of all five plastics, captured at a range of sensor to material distances, to train a classifier that achieves 96% accuracy on a test dataset. To extend the generality and provide insight into the classification process, we fit the ToF histogram data to a physics-based model that differentiates between surface scattering and subsurface scattering. Three optical parameters of the ratio of direct to subsurface intensity, the object distance, and the time constant of the subsurface exponential decay are used as features for a classifier that achieves 88% accuracy. Additional measurements at a fixed distance of [Formula: see text] cm showed perfect classification and revealed that Poisson noise is not the most significant source of variation when measurements are taken over a range of object distances. In total, this work proposes optical parameters for material classification that are robust over object distance and measurable by miniature direct time-of-flight sensors designed for installation in smartphones. |
format | Online Article Text |
id | pubmed-10051388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100513882023-03-30 Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor Becker, Cienna N. Koerner, Lucas J. Sensors (Basel) Article We demonstrate a methodology for non-contact classification of five different plastic types using an inexpensive direct time-of-flight (ToF) sensor, the AMS TMF8801, designed for consumer electronics. The direct ToF sensor measures the time for a brief pulse of light to return from the material with the intensity change and spatial and temporal spread of the returned light conveying information on the optical properties of the material. We use measured ToF histogram data of all five plastics, captured at a range of sensor to material distances, to train a classifier that achieves 96% accuracy on a test dataset. To extend the generality and provide insight into the classification process, we fit the ToF histogram data to a physics-based model that differentiates between surface scattering and subsurface scattering. Three optical parameters of the ratio of direct to subsurface intensity, the object distance, and the time constant of the subsurface exponential decay are used as features for a classifier that achieves 88% accuracy. Additional measurements at a fixed distance of [Formula: see text] cm showed perfect classification and revealed that Poisson noise is not the most significant source of variation when measurements are taken over a range of object distances. In total, this work proposes optical parameters for material classification that are robust over object distance and measurable by miniature direct time-of-flight sensors designed for installation in smartphones. MDPI 2023-03-22 /pmc/articles/PMC10051388/ /pubmed/36992035 http://dx.doi.org/10.3390/s23063324 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Becker, Cienna N. Koerner, Lucas J. Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title | Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title_full | Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title_fullStr | Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title_full_unstemmed | Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title_short | Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor |
title_sort | plastic classification using optical parameter features measured with the tmf8801 direct time-of-flight depth sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10051388/ https://www.ncbi.nlm.nih.gov/pubmed/36992035 http://dx.doi.org/10.3390/s23063324 |
work_keys_str_mv | AT beckerciennan plasticclassificationusingopticalparameterfeaturesmeasuredwiththetmf8801directtimeofflightdepthsensor AT koernerlucasj plasticclassificationusingopticalparameterfeaturesmeasuredwiththetmf8801directtimeofflightdepthsensor |