DescriptionThree different out of many aspects of the use of machine vision in the industry will be highlighted: There is the challenge to move scientific efforts to the practical given factors in manufacturing environments. How the community of machine vision is established in the economy. At least what is the moving spirit of a faculty to promote R&D. In order to successfully implement a computer vision system within a running industrial process there are many key points to be aware of. There are various barriers and pitfalls associated with some of the interfaces: Timing, material transport, mechanics, environmental pollution (steam, heat, water, and oil), maintenance, and budgetary considerations, to mention a few. The wide field of view necessary when implementing a machine vision system drastically increases the amount of measures required to keep the system in operation. The failure of many MV systems is caused by paying too little attention to minor interface effects. The situation of machine vision community in Austria, which in relation roughly is comparable to the EU, is described: Austria has 8 Mio inhabitants; its income depends on industry, agriculture and tourism. There are about 200 engineers working full time in the R&D field of machine vision. Industrial computer vision takes about 50 %. There are seven university institutes, seven R&D associations and some SME in this field. R&D at the University of Applied Sciences Upper Austria deals with a combination of different scientific/technological areas like sensor system, physics, and machine vision. This R&D supports mainly the local manufacturing industry. Three examples will show the result of the collaboration between different approaches to the given task.
|Period||5 Dec 2007|
|Event title||IVCNZ 07: null|
|Location||Hamilton, NZ, Australia|