Unveiling the Invisible

When thinking about a machine vision system a traditional approach is to imagine a machine capable of seeing what the human eye sees.

However, there are applications where different objects look identical and you still want to distinguish them, or you need to inspect transparent samples looking for the presence/absence of a specific feature, or finally, you desire to classify between different materials but not different colors.

Common machine vision systems fail to work on these examples because the properties of light in the visible spectrum cannot reveal the information necessary for these applications. So how can we unveil the needed “invisible” information?

An answer to this question arises from the possibility of switching the light spectral range where the vision system is working from visible to invisible. Machine vision cameras as well as optics, and lighting allow the acquisition of images in the infrared light spectral range.

Working in the Short-Wavelength-Infrared (i.e.: SWIR) range applications such as distinguishing between different types of plastic, detecting water contamination, or seeing through a semiconductor wafer are possible.

In this webinar, we delve deeper into SWIR cameras, their technology, and the main differences between VIS and SWIR vision systems.

We will then explore examples of SWIR applications, comparing the possibilities offered by SWIR to the more common VIS vision systems.