OPTIMIZED 3-DIMENSIONAL RECOVERY FROM 2-DIMENSIONAL IMAGES BY MEANS OF SINE-WAVE STRUCTURED LIGHT ILLUMINATION

A common problem in manufacturing design is the accurate rendering of a 3-D object into a digitized 3-D representation. Such a rendering can be used to duplicate or modify existing objects as well as perform quality control and object recognition in automated manufacturing operations. A structured light technique that uses a sinusoidal illumination pattern to retrieve 3-D information is presented. This technique requires only one image of a surface area to process the topology and can be accomplished with incoherent light. The sine section technique projects a sinusoidal pattern onto an object and recovers the local slopes (first order), which are then combined to reconstruct the surface topology. Surface variations act to create a wideband frequency modulation (zero to infinite frequency), so an optimum frequency demodulation technique is developed to yield average slopes in local regions of the illuminated area. A reconstruction algorithm is introduced that uses these slopes with minimum mean square error. The performance of this technique appears to be very robust and insensitive to intensity variations. Results are presented for recovery of synthesized surfaces corrupted in altitude by additive colored Gaussian spatial noise. The colored noise is generated with a fractal filter to best emulate real surface topologies.