This paper presents a novel method for matching line segments in images based on pair-wise geometric constraints and matching redundancy. In this study, pairs of line segments satisfying angle and distance constraints are used as matching primitives. To ensure that each extracted line segment is paired with another line segment, the search region of each line segment is gradually grown until it is paired. Initial pair-to-pair correspondences between two images are established using four pair-wise constraints; next, line-to-line correspondences are obtained. To effectively solve the matching conflict in the results, a method of recording the result of line pair matching based on a double-layer matrix is proposed. Based on the double-layer matrix, an effective checking method for the line matching results based on the collinearity constraint and matching redundancy is presented. It fully utilizes redundancy information and considers the collinearity of fragmented line segments. Further, it can effectively separate correct and incorrect matches from the one-to-many, many-to-one, and many-to-many matching results. The proposed method was tested on 12 image pairs from a benchmark of matched-lines, and compared with other state-of-the-art methods. The results demonstrate the superiority of the proposed method due to its higher accuracy and greater recall in challenging cases.

本文提出了一种基于成对几何约束和匹配冗余度的图像中线段匹配方法。在这项研究中，将满足角度和距离约束的线段对用作匹配图元。为了确保每个提取的线段与另一个线段配对，每个线段的搜索区域将逐渐增长，直到配对为止。使用四个成对约束建立两个图像之间的初始对对对应关系。接下来，获得线对线的对应关系。为了有效解决结果中的匹配冲突，提出了一种基于双层矩阵的线对匹配结果记录方法。基于双层矩阵，提出了一种基于共线性约束和匹配冗余度的在线匹配结果有效检查方法。它充分利用了冗余信息，并考虑了分段线段的共线性。此外，它可以有效地从一对多，多对一和多对多匹配结果中分离正确和不正确的匹配。在以匹配线为基准的12对图像上测试了该方法，并与其他最新方法进行了比较。结果证明了该方法的优越性，因为它具有更高的准确性和在挑战性情况下的更大召回率。多对一和多对多匹配结果。在以匹配线为基准的12对图像上测试了该方法，并与其他最新方法进行了比较。结果证明了该方法的优越性，因为它具有更高的准确性和在挑战性情况下的更大召回率。多对一和多对多匹配结果。在以匹配线为基准的12对图像上测试了该方法，并与其他最新方法进行了比较。结果证明了该方法的优越性，因为它具有更高的准确性和在挑战性情况下的更大召回率。