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Curve features formed by irregular edges are common in real building images, and effective extraction and matching of curves in images is important for the recovery of real architectural scenes. However, existing curve extraction and matching algorithms are highly specific and difficult to be directly applied to 3D reconstruction of building images with viewpoint variations. Therefore, a full-flow algorithm for curve extraction and matching is proposed in this paper for building images with viewpoint differences. Firstly, the Canny edge detection optimisation algorithm is used to obtain the target contours, and the closed contours are collated to obtain reliable curves with definite endpoints. Then the curve pairs are constructed using the geometric relationships of the curve endpoints, multiple sets of simulated images are set to estimate the best affine transformation parameters, and the image pairs are pre-transformed to obtain corresponding intersections. Finally, the corresponding curves are determined according to the intersection matching results. Experiments using image pairs with different imaging conditions show that the proposed algorithm can overcome the image viewpoint variations and achieve extraction and matching of curves in building images, with good robustness.
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