Contour-based Historical Building Image Matching

With the rapid development of the city, huge temporal and spatial changes have taken place in buildings and surrounding scenes at the same location. At present, people generally lack the technical means to understand the knowledge related to the protection of urban architecture, which leads to the lack of publicity and education of the relevant contents. This is the reason why the architectural heritage is gradually forgotten by the public. So it is an effective means to enhance public awareness and protection of urban history through the comparison of images of historical buildings in different periods. In this paper, based on the typical characteristics of urban buildings images, a contour-based historical building image matching algorithm is proposed. We improved edge detection algorithm with a new operator, meanwhile, used a local threshold automatic adjustment strategy. Before matching, we aggregated short lines which can be aggregated to highlight image features and improve the matching rate. The algorithm can accurately match the images of different historical periods with some differences by effectively extracting and matching the building contours. The experiments show that, compared with the comparison algorithm, our proposed algorithm is more sensitive to gradient changes in multiple directions, and has better effects in detail edge extraction.