Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Becker, Cienna N., Koerner, Lucas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1785014874156302336
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