To realize stable wide-baseline matching for structured scenes with low texture regions, a new matching method based on line intersection features (LIFS) is proposed, which combines the robustness of line feature and distinctiveness of keypoint’s descriptor. First, detect lines and compute line intersections. Second, line intersections from perspective projection of parallel lines or skew lines are filtered by parallel lines clustering and coplanar constraint which increases the stability and accuracy of line intersections. Third, local non maxima suppression is used to limit the intersections close to each other. Fourth, feature scales are computed for LIFS by simply utilizing the geometry distribution of intersections and endpoints of intersection lines. Finally, SURF descriptors are computed for LIFS in the computed scales and thus scale and rotation invariance is achieved. Experiment results show that compared with traditional matching method based on local features, the proposed method is more robust to image noise and illumination change. Besides, the proposed method has invariance to scale and rotation change and a certain degree of viewpoint change, providing an effective wide baseline matching method for images of structured scenes.