August 08, 2017 Volume 13 Issue 30

Electrical/Electronic News & Products

Designfax weekly eMagazine

Subscribe Today!
image of Designfax newsletter

Buyers Guide


View Archives


Manufacturing Center
Product Spotlight

Modern Applications News
Metalworking Ideas For
Today's Job Shops

Tooling and Production
Strategies for large
metalworking plants

Cool Tools: You'll FLIP over this inspection system

Who doesn't like a little flexibility these days? The L.S. Starrett Company has just introduced the HVR100-FLIP, an innovative large field-of-vision (FOV) Benchtop Vision Measurement System that can be used in either a vertical or horizontal orientation and features a high-resolution digital video camera and minimal optical distortion for accurate FOV measurements of up to 90 mm (3.65 in.). The changeable orientation lends itself to an extremely wide array of applications, from flat parts such as gaskets and seals to turned and threaded parts. Includes a 24-in. LCD touch-screen monitor, LED ring light, and motorized drive. Auto Part Recognition can be set to recognize and inspect a part in a few seconds.
Click here to learn more.

World's first solid-state 3D LiDAR IC receives two CES 2018 Innovation Awards

LiDAR laser surveying tech is now available to the masses. LeddarTech is the developer and owner of Leddar, a patented solid-state LiDAR sensing technology that constitutes a novel approach to light detection and ranging. Their product recently one two CES 2018 Innovation Awards in the categories of "Embedded Technologies" and "Vehicle Intelligence and Self-Driving." Up to now, this high-resolution 3D-mapping technology has been very expensive to incorporate into planes, autonomous cars, and drones. This advancement should help push forward large-scale production of automotive-grade LiDAR at an affordable price for mass-market vehicles.
Learn more about this exciting technology.

MEMS inertial accelerometers for drones and more

The Silicon Designs Model 1525 Series tactical-grade MEMS inertial accelerometer family is ideal for zero-to-medium frequency instrumentation applications that require high repeatability, low noise, and maximum stability, including tactical guidance systems, navigation and control systems (GN&C), AHRS, unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), remotely operated vehicles (ROVs), robotic controllers, flight control systems, and marine- and land-based navigation systems. They may also be used to support critical industrial test requirements, such as those common to agricultural, oil and gas drilling, photographic and meteorological drones, as well as seismic and inertial measurements.
Click here to learn more.

First 7-axis motion and pressure sensor

TDK has announced the availability of the InvenSense ICM-20789 MEMS 7-axis integrated inertial device, combining a 3-axis gyroscope, 3-axis accelerometer, and an ultra low-noise MEMS capacitive barometric pressure sensor. The ICM-20789 features a single small footprint, with the industry’s lowest pressure noise of 0.4Pa RMS and excellent temperature stability with a temp coefficient of +/-0.5 Pa/°C. Applications include: drones and flying toys; smart watches, wearables, activity monitoring; motion-based gaming controllers; virtual reality headsets and controllers; and indoor and outdoor navigation.
Click here to learn more.

Energy Harvesting Applications Design Kit (limited release)

AVX has announced the limited release of its new Energy Harvesting Application Design Kit. The kit features a wide range of low-loss components hand-selected to provide engineers with ideal solutions for energy storage, blocking, IC support, output filtering, and external connections in thermoelectric generators, solar cells, piezoelectric devices, and micro wind turbines. Parts include MLCCs, supercapacitors, Schottky diodes, inductors, and connectors. The kit also comes with a booklet that provides users with a brief introduction to energy harvesting and additional information about the components it contains.
Click here to learn more.

New multi-turn sensors with a clutch

Novotechnik, U.S. introduces the ML Series of Multi-Turn Rotary Sensors. These sensors feature a unique friction clutch instead of the end-stops typically found on mechanical multi-turn sensors. The clutch produces a click sound to let users know they have reached end-of-range, and it permits continued turn past end-scale. Compare this feature to a device simply breaking as it is turned past its end-stops. Compact in size, ML Series sensors have a 1/2-in.-sq profile and include models with 6, 10, 25, 50, or 100 turns. Applications include forklifts, sliding gates, electric drive feedback, compactors, and medical devices.
Click here to learn more.

Multi-switch detection interface for automotive

Automotive body control modules (BCMs) are electronic control units that manage numerous vehicle comfort, convenience, and lighting functions, including door locks, windows, chimes, closure sensors, interior and exterior lighting, wipers, and turn signals. John Griffith, Automotive Systems Engineer, Texas Instruments, runs through the benefits -- including significant overall power savings -- of incorporating these devices into automotive designs.
Read the full article.

Cool Tools: Babysitter for equipment now includes thermal monitoring

Fluke has expanded the capabilities of its Condition Monitoring system to include thermal monitoring with the addition of the new Fluke 3550 FC Thermal Imaging Sensor. Maintenance managers can now collect a more comprehensive variety of key-indicator data -- thermal imaging, voltage, current, temperature, and power -- on critical equipment to build a real-time picture of an asset’s condition. Alarms can be set to notify technicians via their mobile phones when specific measurement thresholds have been hit. Machine builders might suggest this system when they sell applicable units.
Click here to learn more.

Simplify thermal management, handle high surges

Littelfuse has introduced two new series of High Temperature Alternistor Triacs. With a maximum junction temperature of 150-deg C, the 16A QJxx16xHx Series and 25A QJxx25xHx Series are designed for use as AC switches, helping circuit designers address overheating challenges in AC power control applications with limited or no heat sinking. Applications include: heater control in coffeemakers; tankless water heaters and infrared heaters; AC solid-state relays; dimmers for incandescent and LED lighting; motor speed control in kitchen appliances and power tools; and compressor motor control in light industrial applications.
Click here to learn more.

Cool Tools: Wireless pocket oscilloscope

Saelig has introduced the IkaScope WS200, a pen-shaped battery-powered wireless oscilloscope that streams captured signals to almost any Wi-Fi-connected screen. This tool offers a 30-MHz bandwidth with its 200-MSa/s sampling rate, and the maximum input is +/-40 Vpp. It provides galvanically isolated measurements even when a USB connection is charging the internal battery. The IkaScope WS200 will work on desktop computers (Windows, Mac, and Linux) as well as on mobile devices like tablets or smartphones (iOS and Android Q4 2017). Application software can be downloaded for whichever platform is needed.
Click here to learn more.

Multi-axis robotic controller

Aerotech’s HEX RC is a 6-axis motion controller ideal for controlling robotic systems like hexapods. It is 4U rack-mountable and compatible with the Automation 3200 (A3200) motion platform. A high-performance processor provides the intense computing power needed to run up to 32 axes, perform complex, synchronized motion trajectories, manipulate I/O, and collect data at high speeds. This unit features 6 axes of drives capable of controlling any combination of brush, brushless, or stepper motors (both current loop and servo loop closures). An optional 6-axis jog pendant permits easy, manual control of the positioning system.
Click here to learn more.

Using natural refrigerants in cooling system design

The use of natural refrigerants is on the rise, creating a new set of challenges for cooling system design. You can optimize safety and efficiency by understanding the implications of the trend on component design and selection. This new white paper from Sensata Technologies provides an overview of methods used to mitigate these technical challenges as well as a look at some of the HVAC and refrigeration hardware and safety technologies required, especially pressure switches and pressure sensors.
Read the white paper (no registration required).

Compact touchless position sensors

TFD Series touchless linear position sensors from Novotechnik provide wear-free operation in tight spaces for measurement of short stroke lengths. They use a magnetic position marker to provide a touchless measurement range of 0 to 14, 24, or 50 mm (depending on model). These sensors make measurements through air and non-magnetic materials. Applications include textile machinery, packaging machinery, sheet metal machinery, medical applications, marine, mobile engine management systems, industrial trucks, construction machinery, and agricultural and forestry machinery.
Click here to learn more.

Connectors: High-current DC power in compact design

Amphenol Industrial Products Group now offers a versatile connection system that distributes high-current DC power in a compact design. Designed to connect wire to wire, wire to board, and busbar terminations, the Amphe-PD series distributes higher currents with less heat than similar-sized connectors on the market. Ideal for use in datacenter equipment, robotics, and industrial automation, the Amphe-PD series connectors offer wire terminations ranging from 12 AWG to 4 AWG.
Click here to learn more.

Cool Tools: Wireless digital micrometer

The new 40 EWRi is the latest addition to Mahr's Integrated wireless family of products, including digital calipers, indicators, and depth gages, which allow users to measure faster, more easily, and more reliably. Measurement data is transferred to an i-Stick on a computer without any interfering data cables, and MarCom software makes data acquisition simple: Just take a measurement and transmit measuring data directly into MS Excel or via a keyboard code into any Windows program or existing SPC application.
Click here to learn more.

New system can automatically retouch cellphone images and display result in real time -- before you take the photo

By Larry Hardesty, MIT

The data captured by today's digital cameras is often treated as the raw material of a final image. Before uploading pictures to social networking sites, even casual cellphone photographers might spend a minute or two balancing color and tuning contrast using one of the many popular image-processing programs now available.

Last week at Siggraph, the premier digital graphics conference, researchers from MIT's Computer Science and Artificial Intelligence Laboratory and Google presented a new system that can automatically retouch images in the style of a professional photographer. It's so energy efficient, however, that it can run on a cellphone, and it's so fast that it can display retouched images in real time, so that the photographer can see the final version of the image while still framing the shot.

The same system can also speed up existing image-processing algorithms. In tests involving a new Google algorithm for producing high-dynamic-range images, which capture subtleties of color lost in standard digital images, the new system produced results that were visually indistinguishable from those of the algorithm in about one-tenth the time -- again, fast enough for real-time display.

A new system can automatically retouch images in the style of a professional photographer. It can run on a cellphone and display retouched images in real time. [Courtesy of the researchers: Edited by MIT News]





The system is a machine-learning system, meaning that it learns to perform tasks by analyzing training data; in this case, for each new task it learned, it was trained on thousands of pairs of images, raw and retouched.

The work builds on an earlier project from the MIT researchers, in which a cellphone would send a low-resolution version of an image to a web server. The server would send back a "transform recipe" that could be used to retouch the high-resolution version of the image on the phone, reducing bandwidth consumption.

"Google heard about the work I'd done on the transform recipe," says Michaël Gharbi, an MIT graduate student in electrical engineering and computer science and first author on both papers. "They themselves did a follow-up on that, so we met and merged the two approaches. The idea was to do everything we were doing before but, instead of having to process everything on the cloud, to learn it. And the first goal of learning it was to speed it up."

VIDEO: Deep bilateral learning for real-time image enhancement.

Short cuts
In the new work, the bulk of the image processing is performed on a low-resolution image, which drastically reduces time and energy consumption. But this introduces a new difficulty, because the color values of the individual pixels in the high-res image have to be inferred from the much coarser output of the machine-learning system.

In the past, researchers have attempted to use machine learning to learn how to "upsample" a low-res image, or increase its resolution by guessing the values of the omitted pixels. During training, the input to the system is a low-res image, and the output is a high-res image. But this doesn't work well in practice; the low-res image just leaves out too much data.

Gharbi and his colleagues -- MIT professor of electrical engineering and computer science Frédo Durand and Jiawen Chen, Jon Barron, and Sam Hasinoff of Google -- address this problem with two clever tricks. The first is that the output of their machine-learning system is not an image; rather, it's a set of simple formulae for modifying the colors of image pixels. During training, the performance of the system is judged according to how well the output formulae, when applied to the original image, approximate the retouched version.

Taking bearings
The second trick is a technique for determining how to apply those formulae to individual pixels in the high-res image. The output of the researchers' system is a three-dimensional grid, 16 x 16 x 8. The 16 x 16 faces of the grid correspond to pixel locations in the source image; the eight layers stacked on top of them correspond to different pixel intensities. Each cell of the grid contains formulae that determine modifications of the color values of the source images.

That means that each cell of one of the grid's 16 x 16 faces has to stand in for thousands of pixels in the high-res image. But suppose that each set of formulae corresponds to a single location at the center of its cell. Then any given high-res pixel falls within a square defined by four sets of formulae.

Roughly speaking, the modification of that pixel's color value is a combination of the formulae at the square's corners, weighted according to distance. A similar weighting occurs in the third dimension of the grid, the one corresponding to pixel intensity.

The researchers trained their system on a data set created by Durand's group and Adobe Systems, the creators of Photoshop. The data set includes 5,000 images, each retouched by five different photographers. They also trained their system on thousands of pairs of images produced by the application of particular image-processing algorithms, such as the one for creating high-dynamic-range (HDR) images. The software for performing each modification takes up about as much space in memory as a single digital photo, so in principle, a cellphone could be equipped to process images in a range of styles.

Finally, the researchers compared their system's performance to that of a machine-learning system that processed images at full resolution rather than low resolution. During processing, the full-res version needed about 12 gigabytes of memory to execute its operations; the researchers' version needed about 100 megabytes, or one-hundredth as much. The full-resolution version of the HDR system took about 10 times as long to produce an image as the original algorithm, or 100 times as long as the researchers' system.

"This technology has the potential to be very useful for real-time image enhancement on mobile platforms," says Barron. "Using machine learning for computational photography is an exciting prospect but is limited by the severe computational and power constraints of mobile phones. This paper may provide us with a way to sidestep these issues and produce new, compelling, real-time photographic experiences without draining your battery or giving you a laggy viewfinder experience."

Published August 2017

Rate this article

[New system can automatically retouch cellphone images and display result in real time -- before you take the photo]

Very interesting, with information I can use
Interesting, with information I may use
Interesting, but not applicable to my operation
Not interesting or inaccurate

E-mail Address (required):


Copyright © 2017 by Nelson Publishing, Inc. All rights reserved. Reproduction Prohibited.
View our terms of use and privacy policy