For many years, pet food manufacturers have used machine vision software to verify the presence of unique characters, codes, colors and graphic shapes on packaging for dog and cat food. Today, however, these companies can complement this process by also verifying the presence of a dog or cat image on the packaging using deep learning vision software.

Many image processing applications depend on varying working distances. As more and more production lines should no longer only operate profitably for mass production but also in small series, the adaptation to new products and therefore varying working distances must be easy and quick to manage.

Short cycle times, little scrap, minimal stock-keeping - the factory of the future is networked and highly economical. An important component here is industrial image processing.

Rough and inhospitable, extremely hot or cold, fire or explosion hazard. Robots for routine and ad-hoc safety checks in unmanned systems are used wherever people are reluctant to be present.

Scientists at Nanyang Technological University, Singapore (NTU Singapore) have developed a robot that can independently assemble the individual components of a chair without interruption.

Today, environmental perception with 3D camera data enables many innovative applications that could previously only be done by humans. Robotics is therefore enabled to recognize objects in a human-like manner and to react independently to different situations.

Industrial camera feature sets constantly evolve. Although users can import these new functions themselves, they have no influence on the range of functions.

Once upon a time, color vision technology was limited to large manufacturers with big budgets and lots of in-house technical expertise. But, recent advancements in cameras, lighting and software have made color vision more affordable, less complex and easier to use on assembly lines.

In many automotive parts, a small defect can cause big problems. This explains why Tier 1 suppliers increasingly use machine vision to inspect parts used for steering, air bags, seat belts, brakes, electronic controls and exhaust.

Ordinarily, parts are presented to a robot for pick up at fixed locations, the escapement of a feeder bowl, for example, or the pockets of a thermoformed tray. To save space and eliminate the cost of trays and feeders, manufacturers would like a robot to pick randomly oriented parts out of a bin, box or tote.