Digital 3D imaging can benefit from advances in VLSI technology in order to accelerate its deployment in many fields like visual communication and industrial automation. High-resolution 3D images can be acquired using laser-based vision systems. With this approach, the 3D information becomes relatively insensitive to background illumination and surface texture. Complete images of visible surfaces that are rather featureless to the human eye or a video camera can be generated. Intelligent digitizers will be capable of measuring accurately and simultaneously colour and 3D.

COLOUR 3D IMAGING TECHNOLOGY

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.

LASER SENSORS FOR 3D IMAGING

The state of the art in laser spot position sensing methods can be divided into two broad classes according to the way the spot position is sensed. Among those, one finds continuous response position sensitive detectors (CRPSD) and discrete response position sensitive detectors (DRPSD)

DISCRETE RESPONSE POSITION SENSITIVE DETECTORS (DRPSD)

DRPSD on the other hand comprise detectors such as Charge Coupled Devices (CCD) and arrays of photodiodes equipped with a multiplexer for sequential reading. They are slower because all the photo-detectors have to be read sequentially prior to the measurement of the location of the peak of the light distribution. DRPSDs are very accurate because of the knowledge of the distribution but slow. Obviously, not all photo-sensors contribute to the computation of the peak. In fact, what is required for the measurement of the light distribution peak is only a small portion of the total array. Once the pertinent light distribution (after windowing around an estimate around the peak) is available, one can compute the location of the desired peak very accurately.

CONCLUSION

The results obtained so far have shown that optical sensors have reached a high level of development and reliability those are suited for high accuracy 3D vision systems. The availability of standard fabrication technologies and the acquired know- how in the design techniques, allow the implementation of optical sensors that are application specific: Opto-ASICs.

The trend shows that the use of the low cost CMOS technology leads competitive optical sensors. Furthermore post-processing modules, as for example anti reflecting coating film deposition and RGB filter deposition to enhance sensitivity and for colour sensing, are at the final certification stage and will soon be available in standard fabrication technologies. The work on the Colorange is being finalized and work has started on a new improved architecture.