Abstract
A new algorithm is presented for estimating speed from roadside cameras in uncongested traffic, congested traffic, favorable weather conditions, and adverse weather conditions. Individual vehicle lanes are identified and horizontal vehicle features are emphasized by using a gradient operator. The features are projected into a one-dimensional subspace and transformed into a linear coordinate system by using a simple camera model. A correlation technique is used to summarize the movement of features through a group of images and estimate mean speed for each lane of vehicles.