Abstract
The concept of an object is central to the solution approach in Sect. 1.5. Indeed, it is decisive for the nature of industrial image processing since its purpose is always to gather information about objects existing in the real world represented in image scenes. In the introductory example in Sect. 1.6 and throughout Chap. 3 on positioning we have frequently used segmentation methods, i.e. algorithms which isolate objects from the scene. In these sections we have simply assumed that such methods exist and achieve the desired effects. Over time a number of such methods have been developed. The most important and most commonly used will be introduced in this chapter.
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Notes
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We use σg here because it is commonly associated with the standard deviation; strictly speaking it should be s.
- 3.
There will of course be some inevitable overhead, but for a comparison of the methods one can roughly assume that speed-up is linear to the reduction of the number of points.
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Demant, C., Garnica, C., Streicher-Abel, B. (2013). Overview: Segmentation. In: Industrial Image Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33905-9_4
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