An efficient and robust line segment matching approach based on LBD descriptor and pairwise geometric consistency

We present a line matching algorithm which utilizes both the local appearance of lines and their geometric attributes. To overcome the problem of segment fragmentation and geometric variation, we extract lines in the scale space. To depict the local appearance of lines, we design a novel line descriptor called Line Band Descriptor (LBD). To evaluate the pairwise geometric consistency, we define the pairwise geometric attributes between line pairs. Then we built a relational graph for candidate line matches and employ a spectral technique to solve this matching problem efficiently. The advantages of the proposed algorithm are as follows: (1) it is robust to image transformations because of the multi-scale line detection strategy; (2) it is efficient because the designed LBD descriptor is fast to compute and the appearance similarities reduce the dimension of the graph matching problem; (3) it is accurate even for low-texture images because of the pairwise geometric consistency evaluation. (C) 2013 Elsevier Inc. All rights reserved.