A mobile mapping system which integrates the global positioning system (GPS) and stereo cameras was developed by the Center for Mapping of the Ohio State University. This system was calibrated using the bundle adjustment with the relative orientation constraints. To extract the useful data from those images, a three-step image matching method based on the epipolar geometry was developed: first, the approximated position is estimated from the system geometry; second, the cross correlation method with the significant maximal coefficient was used. A variable size of template is employed to find the significant maximal correlation coefficient. Third, least squares matching was used to have the sub pixel accuracy. Using this matching method, the point, profile and surface can be measured by selecting points in a single image of a stereo pair. Finally, this technique is extended to extract three dimensional edges by line following. All data captured by the mobile mapping system are available in a global coordinate system.