Near-IR Light Measurement Software

Radiant Vision Systems, Test & Measurement

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Part of the Radiant Vision Systems family of automated photometric test and measurement software, the near-infrared light measurement software module (TT-NIRI) provides all of the benefits of Radiant’s TrueTest software test sequencing platform to efficiently perform image-based measurements of 940 nm near-infrared (near-IR or NIR) LEDs, lasers, and Diffractive Optical Elements (DOE) used for:

     •   Facial and gesture recognition
     •   Eye tracking and iris detection
     •   Automotive LiDAR for autonomous vehicle sensing
     •   Multimodal sensing for device gesture and motion control
     •   Other non-visible 3D sensing applications

Because NIR emissions are not perceived by human vision, measuring NIR light sources is critical for safe (in accordance with standards such as IEC60825-1 and IEC 62471) and accurate 3D sensing performed by NIR-based facial ID devices. In facial recognition, emissions from NIR lasers may be distributed in patterns using DOE to enable sensing of three-dimensional features. In devices using DOE technology, diffracted light casts an array of tiny invisible dots across the user’s face, creating a 3D map. Each dot must be accurately positioned (correct angle, inclination, azimuth) and emitted with sufficient radiant intensity (W/sr) to be properly reflected back and “understood” by the device’s infrared sensor.

Paired with Radiant’s Fourier-optic NIR Intensity Lens, the TT-NIRI software offers comprehensive radiometric data on DOE dot patterns and dot values, which cannot be acquired using alternative methods such as casting the DOE pattern against a wall or other Lambertian surface. Regardless of the DOE dot pattern, position, shape, or size, the TT-NIRI software automatically identifies each dot and outputs data for each dot’s angle of location (azimuth, inclination), maximum intensity, uniformity, and flux. Radiant’s TT-NIRI near-IR light measurement software is capable of both flood distribution measurement (analyzing uniformity, hot spots, fall off, and other aspects of the source) as well as capturing comprehensive dot statistics for evaluating DOEs.

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