3-dimensional surface imaging using Active Wavefront Sampling

Abstract

A novel 3D surface imaging technique using Active Wavefront Sampling (AWS) is presented. In this technique, the optical wavefront traversing a lens is sampled at two or more off-axis locations and the resulting motion of each target feature is measured. This target feature image motion can be used to calculate the feature's distance to the camera. One advantage of this approach over traditional stereo techniques is that only one optical train and one sensor can be used to obtain depth information, thereby reducing the bulk and the potential cost of the equipment. AWS based systems are also flexible operationally in that the number of sampling positions can be increased or decreased to respectively raise the accuracy or to raise the processing speed of the system. Potential applications include general machine vision tasks, 3D endoscopy, and microscopy. The fundamental depth sensitivity of an AWS based system will be discussed, and practical implementations of the approach will be described. Algorithms developed to track target features in the images captured at different aperture sampling positions will be discussed, and a method for calibrating an AWS based method will also be described.