Stereoscopic Light Stripe Scanning: Interference Rejection, Error Minimization and Calibration

Abstract

This paper addresses the problem of rejecting interference due to secondary specular reflections, cross-talk and other mechanisms in an active light stripe scanner for robotic applications. Conventional scanning methods control the environment to ensure the brightness of the stripe exceeds that of all other features. However, this assumption is likely to be violated for a robot operating in an uncontrolled environment. Robust scanning methods already exist, but suffer from problems including assumed scene structure, acquisition delay, lack of error recovery, and incorrect modeling of measurement noise. We propose a robust technique that overcomes these problems, using two cameras and knowledge of the light plane orientation to disambiguate the primary reflection from spurious measurements. Unlike other robust techniques, our validation and reconstruction algorithms are optimal with respect to sensor noise. Furthermore, we propose a procedure to calibrate the system using measurements of an arbitrary non-planar target, providing robust validation independently of ranging accuracy. Finally, our robust techniques allow the sensor to operate in ambient indoor light, allowing color and range to be implicitly registered. An experimental scanner demonstrates the effectiveness of the proposed techniques. Source code and sample data are provided in the multimedia extensions.

The design, implementation, and validation of a 3D laser light-sectioning scanner for biomedical purposes

“…There exists a variety of different techniques for acquiring 3D models of objects, all with a wide range of hardware costs, and differing levels of achievable accuracy and detail in the captured geometric models. Stereoscopic image-based techniques [10], structured light [11,12] and laser light-sectioning methods [13,14], time-of-flight range finders, and shape-from-silhouette algorithms [15], are all methods which have been studied in recent years. With advances in camera technology and computing power, it is becoming more and more possible to create such instrumentation both economically, and for specific applications.…”

“…Occlusions may make it difficult to determine which imaged stripe center corresponds to which illuminating stripe [19] therefore complex image processing software must be able to distinguish between two different lines [13]. Solutions to this challenge currently being researched 15 include a technique called Multistripe Laser Technology (MLT) [11,12], and techniques which use different colours to disambiguate the stripes [12,13]. Sensitivity to ambient light remains an issue, and certain assumptions have to be made about the object's surface smoothness in order to use these techniques [13,19].…”