About This Webinar
In recent years, growth in multispectral and hyperspectral imaging has enabled new applications for vision system designers and expanded the range of imaging applications that can be addressed. Advances in spectral illumination have enabled this growth. Illumination is critical in any machine vision system, particularly in multispectral and hyperspectral imaging systems where lighting is fundamental to system performance. With the correct lighting, significantly more data can be gathered, allowing for simultaneous qualitative and quantitative analysis, which was previously not feasible.
This presentation discusses multispectral and hyperspectral imaging techniques as well as key characteristics of spectral illumination including wavelength, intensity, control, and commercial considerations. Branch uses case studies to demonstrate technical considerations when employing these techniques.
*** This presentation premiered during the
2023 Vision Spectra Conference. For more information on Photonics Media conferences, visit
events.photonics.com.
About the presenter
Matthew Branch, Ph.D., is an application engineer at ProPhotonix Ltd., an LED light and laser diode module manufacturer of machine vision lighting systems worldwide. Educated in the field of semiconductor physics, Branch now also has over 15 years of experience in the field of LED industrial and machine vision lighting. He is based in the company’s LED manufacturing facility in Cork, Ireland and on a day-to-day basis, he manages many of the product lifecycles within the ProPhotonix product offering.
Supporting the sales team within ProPhotonix, Branch works closely with end-users to specify the correct LED or laser-based system suitable for their application. This requires a thorough understanding of the capabilities of the ProPhotonix product offerings and how to best apply them for maximum results. In the case of custom or OEM products, he works closely with customers at a very early stage to translate their product requirements into a realistic and cost-effective development proposal.