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dimension G


Imaging in 3D is billed as one of the most promising growth areas in machine vision at

the moment, but is the hype justified? Greg Blackman finds out

o to the Vision show in Stuttgart in November or any number of automation shows and you’ll see 3D

vision technologies in action. Robotic bin picking is a popular demo, whereby a box of randomly orientated parts is rapidly emptied by an industrious robot arm controlled by stereovision or a triangulation approach of some kind. 3D vision is oſten quoted as one of the stronger growth areas in machine vision, but is it really such a significant technology? Te first thing to say, as Arnaud Lina,

processing team manager for analysis tools at Matrox Imaging, rightly points out, is that 3D imaging solves problems that cannot be solved by 2D imaging. Anything where a volume is required would need 3D and there are a number of areas where 3D systems are installed and operating well. Portioning food is a classic example of where 3D excels, such as filleting

10 Imaging and Machine Vision Europe • June/July 2012

chicken into equal sized pieces. In the timber industry, 3D measurements are made of planks of wood for quality control; in automotive, stereocameras guide robots fitting windshields in vehicles, or laser triangulation is used to generate a 3D profile of car body panels; in semiconductor, the 3D structure of silicon wafers can be measured at a micron scale; and the list goes on. It is, however, quite a young technology relative

to 2D machine vision and still needs to develop. It also isn’t the answer to every vision-related problem. Mark Williamson, director of corporate market development at Stemmer Imaging, comments: ‘Acquiring height information in some applications can be very important, but I would suggest 3D imaging is still very much a niche capability and not needed for many applications.’ Stemmer Imaging conducted a market survey

when it took on LMI’s Gocator 3D sensor, which, according to Williamson, estimates that 3D is currently about 10 per cent of the 2D market. ‘You need to have a reason to go to 3D,’ he says, but adding that, in some cases, 3D can deliver the easiest, most robust solution and that it does solve some key issues. One of the main difficulties with 3D imaging is

its complexity. Williamson states: ‘3D might give more information than 2D, but it also becomes a lot more complicated.’ Tese complications lie in setting up and calibrating the system, as well as

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