3-D Object Recognition Based on Integration of Range Image and Gray-scale Image

In this paper, we propose a practical object recognition system which consists of two functional modules. The first is object extraction module using a range image, and the second is a precise position measurement module using a grayscale intensity image. Both high-reliability and high-accuracy can be achieved by effective image integration. We also propose an idea of stereo vision with random-dot pattern projection as an effective way to obtain a range image. This method enables reliable stereo matching, even for objects with no texture. Through an experiment with real images, we have demonstrated that our system has 99.8% recognition reliability and processing time is approximately 5 seconds per image; as a result, the system can be applied to practical industrial robot vision.