3-D object model recovery from 2-D images using structured light

Three dimensional (3-D) object models are currently used in CAD/CAM, robotics, remote sensing, etc. The models (images) can be either directly acquired by using special devices such as range finders, CTR scanners, etc. or they can be recovered from a series of 2-D images of the object. In this paper, the authors propose a method for determining a set of reference pixels in two simultaneous views of the same object, using two cameras, by projecting a pseudo-random encoded grid on the object. The grid nodes and their encoding values are extracted from 2-D images by applying first a smoothing and then a watershed algorithm. The pseudo-random information encoded in the grid nodes is used to match corresponding sets of points of the two 2-D images. The set of matched points are further used to calculate the disparity of each point of the object surface. Experimental examples illustrate the performance of this simple and elegant technique