Optical 3D Sensors

  • G. Häusler
Chapter
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 556)

Abstract

This chapter is concerned with three-dimensional (3D) image acquisition, including a brief introduction to the problems of two-dimensional image capturing. We emphasize on 3D data because it represents information about the geometrical shape and is therefore often of much greater value than 2D data that represents the local reflectivity only. Geometrical shape is invariant with respect to rotations and shifts, and unaffected by soiling and illumination conditions. Moreover, the shape is the feature that is usually required for inspection purposes. Assuming this to be true, we might ask ourselves why we do not find 3D sensors everywhere? The answer is that video-cameras and computers are seducingly easy to use. Unfortunately, the acquisition of 3D data is much more difficult than the capture of a video image because of deep physical reasons (the optical transfer function of empty space cuts off most of the longitudinal frequencies) and because of technical reasons (the very limited space-bandwidth product of video cameras).

Keywords

Spatial Coherence Sampling Theorem Spot Image Speckle Noise Object Wave 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • G. Häusler

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