The use of industrial vision as part of Industry 4.0 and smart factories has been discussed extensively in recent years, but requires machines to speak the same language.
Machine vision systems consist of several component parts, including illumination, lenses, camera, image acquisition and data transfer, and image processing and measurement software. There are a number of machine vision standards in use which provide commonality for certain parts of the system, but it is also important to consider the system as a whole, including external machine and environmental influences and conditions. Standards are developed by experts of the machine vision industry to ensure high quality and relevance to the sector. However they take time to be developed and ratified for use, and then in turn it can takes time for industry to adopt a new standard. For example, OEM system builders only revisit a design maybe once every five years, so if the standard in use is working appropriately, the design is unlikely to change unless there is a significant performance or price advantage by changing to a new standard. This article will review the adoption of some of the newer standards to emerge and look at some that are in the pipeline as well as an overall system standard.
EMVA1288 is administered by the European Machine Vision Association (EMVA) and is useful for both manufacturers and users of sensors and cameras. It creates transparency by defining reliable and exact measurement procedures as well as data presentation guidelines that makes the comparison of cameras and image sensors much easier. It can be applied to all machine vision cameras. The standard data format features a photon transfer curve, a signal-to-noise ratio curve and a list of measured parameters together with a number of calculated parameters. Users can therefore compare cameras according to the parameters that are most important to their particular application.