Since its inception in the 1980s, machine vision is constantly advancing in optical technology, processors, and software algorithms and making it easier for end-user to use it. so we talk about upcoming trends in machine vision.
Just like in other industries which are benefiting from rapid advancements in technology like big data, cloud, artificial intelligence (AI). Likewise these technologies will also hugely beneficial to manufacturing industries, the three key advances in machine vision for automation will be:
Day by day demand for bulk inspection is increasing which require larger area to be seen by the camera for inspection purpose. 1, 2 and 5 Megapixel cameras continue to lead market but we are also seeing considerable demand of higher resolution sensors such as 12-20 megapixels owing to the requirement of larger inspection area. Earlier multiple cameras were used to cater this requirement but using multiple camera increases a lot of error prone post processing on images which consume huge amount of processing power.
Measuring depth of on object or distance to the object has also turned out to be crucial which was earlier done by using multiple cameras placed at different viewing angles. Now the technology such as stereo vision, time of flight (tof) and leaser triangulation is supported by required advance hardware to meet the requirements.
Traditional methods are still widely used in most food industries due to the unavailability of smart alternatives. Traditional destructive methods are not suitable in today's hypercompetitive marketplace. Consequently, a cost-effective, efficient, rapid, and reliable method is required. In particular, there is a great interest in developing non-destructive optical technologies that have the capability of monitoring in a real-time assessment. Among them, hyper spectral imaging techniques have received ample attention. Hyper spectral imaging systems provide spatial and spectral details; therefore, these systems introduce new sensing facilities that enable improved inspection.
“fabulous machine that have all our senses, all our reasons and think just like we do – you have seen these machine in movies as a friend or foe, now fiction becomes reality”
AI is allowing enterprises to automate inspections that were previously only able to do manually. It efficiently solve complex inspection challenges that are cumbersome or time-consuming to do with traditional rule-based machine vision algorithms.
With deep learning, engineers can train a machine vision system to learn what is an acceptable or unacceptable defect from a data set of reference pictures rather than program the vision system to account for the thousands of defect possibilities.
For example, a pharmaceutical company’s systems
