Dual-band stereo vision based on heterogeneous sensor networks

Abstract

This paper presents an approach of dual-band imagery based on heterogeneous sensor network which consists of infrared and optical sensors, and our approach of imaging reconstructs the three-dimensional shapes of the objects in some special environments such as smog, darkness, glare and so forth. Two dichroic mirrors are used for the construction of the binocular stereo vision system which consists of two optical (visible) and two infrared cameras. We make use of the complementarity between infrared and visible images to form two fused images as the source images of the stereo vision system. A stereo matching algorithm based on dual-band images is proposed as well. We use the gray, gradient direction and gradient magnitude of the pixels taken from the two bands of images to compute the disparity value of each pixel. Experiments show that the stereo matching algorithm is robust and not sensitive to the environmental variations. As a result, the dual-band stereo vision system has a good support for the target recognitions and measurements in different environments, such as all-weather traffic monitoring, searching and rescuing in fires, and so forth.