Sensors on 3D Digitization
Published on Aug 15, 2016
Machine vision involves the analysis of the properties of the luminous flux reflected or radiated by objects. To recover the geometrical structures of these objects, either to recognize or to measure their dimension, two basic vision strategies are available.
Passive vision, attempts to analyze the structure of the scene under ambient light.  Stereoscopic vision is a passive optical technique. The basic idea is that two or more digital images are taken from known locations. The images are then processed to find the correlations between them. As soon as matching points are identified, the geometry can be computed.
Active vision attempts to reduce the ambiguity of scene analysis by structuring the way in which images are formed. Sensors that capitalize on active vision can resolve most of the ambiguities found with two-dimensional imaging systems. Lidar based or triangulation based laser range cameras are examples of active vision technique. One digital 3D imaging system based on optical triangulation were developed and demonstrated.
The auto-synchronized scanner, depicted schematically on Figure 1, can provide registered range and colour data of visible surfaces.
A 3D surface map is captured by scanning a laser spot onto a scene, collecting the reflected laser light, and finally focusing the beam onto a linear laser spot sensor. Geometric and photometric corrections of the raw data give two images in perfect registration: one with x, y, z co-ordinates and a second with reflectance data. The laser beam composed of multiple visible wavelengths is used for the purpose of measuring the colour map of a scene