Abstract
It might appear unusual to start a detailed discussion of the various application areas of industrial image processing with positioning instead of object recognition since an object must first be found before its position can be determined. However, object recognition is a rather broad term and frequently necessitates a multitude of functions to be able to assign objects to a category. Positioning, however, is structurally speaking—not necessarily algorithmically—a rather simple affair as soon as the object in question has been found. The only necessary prerequisite is the segmentation of a reference object. The main reason to begin with this topic is that it represents an absolutely essential “auxiliary science”.
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If one does not want to compute the coordinates of each point using trigonometric functions which would be extremely slow.
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The control system must of course take into account the angle by which the turntable has already been turned in accordance with the ring's orientation, but this takes a lot less effort than capturing the image one more time and determining the position.
References
Gonzalez RC, Woods RE (2008) Digital image processing, 3rd edn. Pearson Education, Upper Saddle River
Parker JR (1994) Practical computer vision using C. Wiley, New York
Russ JC (2007) The image processing handbook, 5th edn. CRC Press, Boca Raton
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© 2013 Springer-Verlag Berlin Heidelberg
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Demant, C., Garnica, C., Streicher-Abel, B. (2013). Positioning. In: Industrial Image Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33905-9_3
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DOI: https://doi.org/10.1007/978-3-642-33905-9_3
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