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Some application fields and inspection solutions require NIR for high wavelengths as well as for normal lighting, to record high-contrast images. Standard industrial cameras quickly reach their limits in that particular scenario, since they require very good lighting conditions to capture useable images. Setting up these light solutions adds tremendous cost and complexity, which in turn leads to rising system costs and deterioration of the price/performance ratio. Industrial cameras with NIR-optimized sensors greatly simplify life for manufacturers facing inspection tasks of this type.
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The NIR-optimized cameras with NIR-optimized 2 MP (CMV2000) and 4 MP (CMV4000) sensors from ams, or the 1.3 MP sensor (EV76C661) from e2V, still manage quantum efficiencies close to 40% in the 850nm range. Compared to non-NIR-optimized cameras, this represents a doubling of the sensitivity value at this wavelength.
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Typical application examples are traffic monitoring installations that need to work in poor lighting conditions and at night, fruit and vegetable inspections to detect damaged spots using location-sensing spectroscopy, and the inspection of solar wafers through electro-luminescence.
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“Near-infrared” (NIR) is the portion of the electromagnetic spectrum directly adjacent to the visible range; therefore it cannot be perceived with the human eye. NIR-optimized industrial cameras are popular for applications that need to utilize this wavelength range, e.g. applications with poor light conditions, such as traffic monitoring. Until now, these applications were only possible with infrared cameras with expensive CCD sensors.
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Now, new CMOS technology can do the job, providing sensors with increased sensitivity in the near-infrared range over 850 nm. It achieves this through the application of a thicker substrate layer (as compared to a monochrome sensor) for the visible spectral range. The new CMOS technology has made NIR optimization affordable, through a line of industrial cameras with excellent sensitivity in the near-infrared, which in turn has boosted their share on the machine vision market.
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