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Plastic Classification Using Optical Parameter Features Measured with the TMF8801 Direct Time-of-Flight Depth Sensor.

Cienna N Becker¹, Lucas J Koerner¹

¹Department of Computer and Electrical Engineering, University of St. Thomas School of Engineering, St. Paul, MN 55105, USA.

Sensors (Basel, Switzerland)

|March 30, 2023

Summary

This summary is machine-generated.

This study presents a novel method for non-contact plastic classification using a low-cost direct time-of-flight (ToF) sensor. The technique achieves high accuracy, paving the way for smart material identification in consumer electronics.

Keywords:

material classification material impulse response function (MIRF)material sensing time of flight (ToF)

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Area of Science:

Optoelectronics
Materials Science
Sensor Technology

Background:

Accurate material identification is crucial for recycling and product safety.
Existing methods often require physical contact or complex equipment.
Miniaturized sensors offer potential for on-device material analysis.

Purpose of the Study:

To develop a non-contact method for classifying different plastic types.
To utilize inexpensive direct time-of-flight (ToF) sensors for material characterization.
To explore physics-based optical parameters for robust classification.

Main Methods:

Employed a direct ToF sensor (AMS TMF8801) to capture light return times from five plastic types.
Collected ToF histogram data across various sensor-to-material distances.
Trained a classifier using ToF data and fitted data to a physics-based scattering model.

Main Results:

Achieved 96% classification accuracy using raw ToF histogram data.
Developed a physics-based model using optical parameters (surface/subsurface scattering ratio, distance, decay time).
This model yielded 88% accuracy and provided insights into scattering mechanisms.

Conclusions:

Direct ToF sensors can effectively classify plastic types non-contact.
Physics-based optical parameters derived from ToF data offer robust material identification.
The methodology is suitable for integration into consumer electronics like smartphones.