Volume 24, Issue 5 | Vision Systems Design

Vision Systems Design Volume 24, Issue 5

Volume 24, Issue 5

May 2019

Vision Systems Design Volume 24, Issue 6

Vision Systems Design Volume 24, Issue 5

Vision Systems Design Volume 24, Issue 4

Vision Systems Design Volume 24, Issue 3

Vision Systems Design Volume 24, Issue 2

Vision Systems Design Volume 24, Issue 1

Vision Systems Design Volume 23, Issue 11

Vision Systems Design Volume 23, Issue 10

Vision Systems Design Volume 23, Issue 9

Content from Volume 24, Issue 5

Figure 1: The solid line shows spectral reflectance curves of blue-colored patch on textile substrates while the dashed line shows the same for paper substrate. A large difference between the curves emerges at wavelengths larger than 660 nm.

How application-specific color calibration impacts multispectral imaging

May 2019 snapshots: Machine learning system assists animal conservation efforts, image sensors for detecting exoplanets, fully-automated test processes for aircraft cockpits, and hyperspectral instruments to study climate change.

Figure 1: In each of Byrne’s three assembly cells, two six-axis robots work with a 4-camera Datalogic machine vision system to pick parts, assemble and inspect outlets. The final pack out cell uses an LMI Gocator 3D snapshot sensor for final inspection.

Machine vision system identifies and locates pickable parts for robotic assembly cell

The vision-guided Hugin drone provides aerial images for emergency responders.

Vision-guided drone supports flood and coastal protection efforts

The MiR200 robot loops around Metro Plastic’s factory floor every 10 minutes, allowing operators to load finished products as soon as they fill a box. This has eliminated clutter and traffic on the floor, reduced the risk of injuries associated with forklift driving, and improved the efficiency of the company’s quality inspections and overall operations.

Autonomous mobile robot improves safety and efficiency at plastic injection molding facility

Figure 1: Canned food, bottles, engine parts, and electronic sub-assemblies may be checked for correct label orientation, fill levels, barcodes, and the presence/absence of components. Such high-speed production systems themselves must also be monitored to diagnose any mechanical failure that may occur.

High-speed cameras target process monitoring applications

Kelzal’s cameras deploy event-based image sensors to enable efficient, high-speed imaging.

Event-based cameras target surveillance, autonomous vehicle applications

Figure 1: Nippon Systemware (NSW) offers an IP core for haze reduction that can be used with both Altera (Intel) and Xilinx devices. The so-called “Haze Reduction Engine” is used to reduce haze or fog in RGB images and is targeted at such applications as networked surveillance cameras and smart vehicles.

Low-cost development tools reduce the cost of embedded vision

Andy Wilson, 1956-2019

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