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Vision Spectra Preview - Autumn 2023

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Here is your first look at the editorial content for the upcoming Autumn issue of Vision Spectra.

Machine Vision Filters

Sputter-coated interference filters from UV, VIS, NIR, and SWIR deliver exemplary performance for demanding machine vision applications. This article will discuss what makes up a good machine vision filter - why having high transmission, steep spectral edges, tightly controlled spectral bands, and deep blocking of unwanted light matters. The article will demonstrate how customized spectral band placement and increased blocking of particular unwanted wavelengths from lasers or the strong spectral lines of industrial lighting can boost contrast. It will also share examples of custom solutions, such as multi-band filters, and how those solutions can improve imaging system performance for a variety of demanding machine vision applications.

Key Technologies: Machine Vision Filters, multi-band filters, sputter coated interference filters


Growth in e-commerce has significantly increased the volume of goods transported, which has put pressure on businesses to maintain quality and throughput in logistics and warehousing scenarios. For companies in this space, industrial automation technologies have become more important than ever before, but as processes evolve and expand, machine vision components must be able to keep pace. This article looks at some common challenges and problems faced in logistics environments and how novel lighting designs and implementations can help overcome these issues to boost productivity, enhance efficiency, and keep costs down while driving revenue. Challenges include barcode reading and OCR through highly reflective plastic wraps and shipping bags and the environmental/employee wellbeing issue of deploying the bright, flashing LEDs required for such applications in open areas around employees.

Key Technologies: LEDs, Lighting for barcode reading and OCR

AI & Supervised vs. Unsupervised AI for inspection

"A recent report by investment bank Goldman Sachs estimated that artificial intelligence may replace the equivalent of 300 million full time jobs. While the recent progress made by language models like ChatGPT has stimulated a fresh wave of fear about new technologies leading to job losses, some see AI assisting, rather than replacing the quality manager.

In this article, Zohar Kantor explains how augmented intelligence differs from traditional understandings of the role of artificial intelligence in quality inspection. Kantor argues that the key driver of technological breakthroughs in this field is not the need or desire to replace workers, but the growing importance of quality in manufacturing. By using advanced deep learning algorithms, QualiSense is developing technology that will reduce the risk of defects in manufacturing production, by automating elements of the process. However, Kantor argues that the end goal will always be to allow the quality manager to retain control, as the model developed by AI will need to harness their unique understanding of the product and the production process. Rather than replace workers, efforts to develop fully autonomous quality inspection systems will most likely fail."

Key Technologies: Artificial Intelligence, deep learning

Vision in Automotive Manufacturing

Automotive manufacturing has long used vision for process control and quality assurance inspections. The rollout of e-mobility and the need to meet tighter emission requirements, however, are creating new challenges. Fortunately, the arrival of more powerful smart cameras and better performing AI have combined to create new capabilities that impact these applications, as an examination of a few examples shows.

Key Technologies: Smart cameras, AI, optical character recognition (OCR), high resolution cameras, vision lighting, embedded edge vision systems

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