What is a CMOS-SWIR Sensor?
SWIR (Short-Wave Infrared) refers to the wavelength region of 900-2500nm. Traditional silicon sensors have an upper limit of approximately 1100nm. SWIR detection often requires camera components made of exotic materials. For example, Indium Gallium Arsenide (InGaAs) sensors (~900-1700nm range) are inherently expensive and often face challenges scaling to smaller pixel pitches and higher resolution arrays.
CMOS (Complementary Metal Oxide Semiconductor) is used in integrated circuits to to convert photons to electrons, in other terms what converts energy to create an image. A pure CMOS-based sensor is capable of SWIR wavelength detection without the use of expensive semiconductor materials, making it a cost-effective technology that enables seamless integration.
What can a quantum photodetecting SWIR camera do?
Medium Material Detection
SWIR wavelengths are absorbed and reflected according to the material, therefore you can detect things hidden in visible light.
Package Component Detection
Certain plastics or objects become transparent using SWIR cameras, useful for fill detection and quality control
Non-invasive Blood Vein Detection
SWIR enables non-invasive bio-signal data to see beyond skin for health diagnostic or secure biometric authentication.
Differing package materials become transparent using SWIR cameras, useful for content inspection and quality control.
Edge Detection is vital to future of machine vision and pattern recognition. Industries ranging from automotive and agriculture to distribution and warehousing can all benefit from accurate edge detection. Edge detection enables AI within vehicles to identify and differentiate the silhouette of a box or bag from that of a pedestrian crossing the street.
Bio-Medical/Health & Biometric
Combining visual and SWIR imaging provides information on skin and tissue surfaces, offering a safer medical diagnostic, health monitoring, and secure biometric solution.
ADAS & AV
Current Advanced Driver Assistance Systems and Autonomous vehicles rely on cameras that fail to provide accurate detection of road and environmental hazards whereas it is possible with SWIR imaging.
Industrial & Machine Vision
The industrial automation and digitization of manufacturing is currently limited by the image data provided by the image sensor hardware used in machine vision systems. Implementing SWIR imaging would assist in decreasing discrepancies.