Automation technology and machine vision are increasingly merging. Our press agent Peter Stiefenhöfer discussed this exciting development with Peter Keppler, Director of Corporate Sales at STEMMER IMAGING.
Computational Imaging (CI) uses data extracted from a series of images acquired under different lighting or optical conditions to create an output image containing the details that are most important to a particular machine vision task. This approach offers powerful advantages over traditional one-shot imaging. It can improve the capability of a camera and reveal image detail not previously possible.
In principle, every image processing system consists of two basic function units: the image source and the image sink. Today compact CMOS cameras are usually used as the image source in the industrial imaging environment. The image sink is the processing unit that extracts results from the image. Currently this will most likely be a classic PC system based on Intel processors and the Windows operating system.
Embedded Vision has been THE trend topic in the industry for some time now. Rarely in the past has a vision technology been ascribed so much change potential. A large number of exciting possible uses for Embedded Vision systems already exist in virtually all branches of industry and daily life. But will this technology really lead to a complete upheaval in machine vision?
Machine vision is a well-established technique across a host of industries, improving quality and efficiency in the manufacturing and processing sectors. Its ability to make inspections reliably and at speed 24/7 makes it an invaluable enabling technology in quality control. Technological advances in machine vision continue to be made rapidly, opening up more and more possibilities.
Gigabit-Ethernet for Machine Vision or, in short, GigE Vision: According to
many experts, the new interface standard and the closely associated generic
software interface GenICam (Generic Interface for Cameras) will give new
impetus to the industrial image processing sector in the near future: The
image processing industry finds itself at a crucial technological watershed!
Hyperspectral imaging provides its users with a high-performance possibility to determine differences in the chemical composition of test objects. This technology opens up interesting applications in areas such as recycling or food production.
Inspection is a critical component of HACCP programs in the food industry. Hyperspectral imaging now provides a powerful complementary approach for the machine vision engineer. Its ability to identify differences in the chemical composition of organic materials opens up major new possibilities for detecting impurities in food products. Most importantly, systems are now available that operate in real time, allowing them to be used on high speed production lines.
Chemical Colour Imaging (CCI) makes complex hyperspectral data on a molecular level usable for machine vision. Hyperspectral imaging systems from STEMMER IMAGING based on a generic, intuitive configurable data processing platform developed by Perception Park make the scientific methods of hyperspectral analysis accessible for everyone and open up new application areas.
When implementing an image processing solution, the selection of suitable illumination is a crucial element in determining the quality of the captured images and can have a huge effect on the subsequent evaluation of the image. Despite this, choosing the best light source for an application is often among the most fraught tasks in image processing and is quite often neglected - to the detriment of the overall system.
There are many different ways of increasing image processing speed. In the
latest version of Common Vision Blox, STEMMER IMAGING has adopted a new
method: offloading parts of the processing to the PC`s graphics card, which
can boost the speed of some functions by up to a factor of 10.