Carnegie Mellon University
file.pdf (221.07 kB)

A Spectro-polarimetric Imager for Intelligent Transportation Systems

Download (221.07 kB)
journal contribution
posted on 1997-01-01, 00:00 authored by Daniel F. Huber, Louis Denes, Martial Hebert, Milton Gottlieb, Boris Kaminsky, Peter Metes
We have built a portable spectro-polarimetric machine vision system that operates at video frame rates. Our system contains only electronically controllable components, including an imaging acousto-optic tunable filter (AOTF), a phase retarder, acceptance and imaging optics, and a standard CCD-based camera. The device operates like an ordinary camera, except that a computer controls the spectral and polarization content of light to be viewed. For example, by sweeping the wavelength over the AOTF's range (visible and near infrared), one can obtain a spectral signature for each pixel in an image. Alternately, the camera can switch between two wavelengths, allowing for high-speed discrimination of closely matched colors in a scene. In addition to digitally controlling the wavelength, our imager uses a liquid crystal retarder to filter images based on polarization signatures of objects. We have implemented a number of algorithms to take advantage of the unique capabilities of our sensor, some of which can be applied to problems specific to transportation systems. We present two image processing applications that highlight the different methods we use to analyze scenes with our system. One application uses spectral processing to locate vegetation in a scene; the second uses polarization signatures to detect glare from hazardous road conditions such as water and ice.




Usage metrics


    Ref. manager