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Imaging and Range Image Processing

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Machine Vision Handbook

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In many industry applications, the image processing tools with input images in 2-D format may find themselves lacking the power of dimensional measurement in a space that has to deal with a third dimension. For an example of typical pick-and-place process on a manufacturing line, a robot tries to grab an unpolished engine block from a bin and the robot controller should give the guidance to the robot arm so that the orientation of the engine block is input to the robot arm prior to its movement. In such a scenario, range information of the engine block, or the depth in the Z-direction, should be part of the input images. The conventional imaging methods for capturing and analyzing grayscale images are inadequate for this type of application.

Range imaging deals with Z-directional data. When many call it 3-D, it is in fact 2.5-D, since we cannot get image data on the negative Z-direction; therefore, it is more pertinent to call it range imaging. There are several techniques that are...

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Michigan-Dearborn, 4901 Evergreen Rd, Dearborn, MI, 48128-1491, USA

    Dr. Dongming Zhao

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  1. Dr. Dongming Zhao
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Correspondence to Dongming Zhao .

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Editors and Affiliations

  1. School of Computer Science and Informatics, Cardiff University, Cardiff, Wales, UK

    Bruce G. Batchelor (Professor Emeritus) (Professor Emeritus)

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© 2012 Springer-Verlag London Ltd.

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Zhao, D. (2012). Imaging and Range Image Processing. In: Batchelor, B.G. (eds) Machine Vision Handbook. Springer, London. https://doi.org/10.1007/978-1-84996-169-1_15

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