Color Image Processing for Navigation: Two Road Trackers

摘要

To build on autonomous vehicle capable of road following, it is necessary tocompute the position and the orientation of the vehicle relative to the road. One way of doing so is to acquire images from a camera on the vehicle and extract some road features from these images. Knowing the geometric transformation between the camera and the ground plane, it is easy to compute the position and the orientation of the vehicle relative to these road features. A system is built to track structured roads, roads that have lane markings, shoulders, and other structures. For these roads, the easiest visual features to track are white lines and the yellow lines. Robust extractors are needed to deal with a variety of roads, light and weather conditions. In the case of the white stripe, we use our knowledge about its shape to extract it. We create a mask with a shape similar to the current white stripe and convolve a search area in the image with it. The maximum correlation gives us the location of the stripe. A large mask is used to reduce the signal/noise ratio, and to be robust in the cases of light and weather variations. Taking into account the current running total during the convolution phases reduces the computational time drastically and so gets a fast operator to track the white stripe. In the case of the yellow stripes, the color is a strong characteristic of this kind of stripe, and the hue is only slightly affected by lighting and weather variations (the image maybe a dark or a light yellow, but it is always a yellow color). The yellow stripe tracker will be based on the hue information. (jhd)