If you are like me, you may be getting confused by the plethora of interface standards that are appearing everywhere in Machine Vision. It started smoothly with Camera Link more than ten years ago. Then came DCAM for Firewire, followed by GigE Vision which paved the way for GenICam (itself divided into 3 modules: GenAPI, GenTL and SFNC), EMVA1288, and now CoaXPress, Camera Link HS and USB3 Vision. Wow, this means a lot of different ways to transfer images from your camera to your PC!
To some, it might appear as if the Automated Imaging Association (AIA), European Machine Vision Association (EMVA) and the Japanese Industrial Imaging Association (JIIA) are in a strange competition to own as many standards as they can. Since the inception of the G3 agreement between these 3 associations in November 2010, proposals for standard activities have exploded. Knowing that the association making the proposal manages the corresponding standard committee, this should not be too surprising. Members of the other 2 organizations can participate in the standard activities, but there is nothing like being in charge. Reality is that better coordination prevents having to re-invent the wheel and participants to these standards have seen the benefits of collaboration within the industry.
Personally, I have been directly involved in the development of some of these MV standards, most notably GigE Vision. My journey in this strange world (where you cooperate with competitors) started in the summer of 2004 when Coreco Imaging was admitted to the GigE Vision temple. Oddly enough, I anticipated it would be difficult to “work with the enemy”, but it turned out that the other participants were equally motivated and interested in advancing this technology. I continue to be amazed by this opportunity to work with gifted engineers from around the globe.
One of my resolutions for 2012 is to share with you some of these committee stories (there is nothing like talking with some of the best machine vision engineers in front of a beer to understand what works and what doesn’t) and hence try to predict where Machine Vision is going. I love hockey and one of my favorite quotes is from Wayne Gretzky:
A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be.
And I certainly want to anticipate where the Machine Vision puck is going so I am ready to catch it!