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This paper proposes a line segment matching method by performing line mapping and unmapping based on point correspondences. The goal of this paper is to improve the accuracy and the robustness of line segment matching for two views, which will be conducive for generating a full single-line structure for image sequences. In this paper, to improve the quantity and quality of line matches, the topological adjacency of a point-line is first introduced for two goals: to find and filter the candidate line segment by resorting to KD-tree data-index structure efficiently in the corresponding image and to leverage the candidate line segment to improve the performance of planar homography. In addition, the shift threshold parameter is theoretically analyzed, and trials are validated to determine the matching degree. Line mapping and unmapping are then used for image sequences to reduce missing matches. The extensive experimental results validate and demonstrate that our method is both more accurate and robust than existing line matching methods for two views under the circumstance of a higher recall rate. In addition, our method contributes in finding full line segments for image sequences using line mapping, with higher completeness of the 3D line model than that obtained by the state-of-the-art methods.