Complex building description and extraction based on Hough transformation and cycle detection

A simple but robust approach for complex building description and extraction from high-resolution remotely sensed imagery based on graph-based shape representation is proposed. Classical approaches for building extraction usually involve a complex grouping process of low-level primitive features and are not robust in the presence of noise. To overcome these drawbacks, this approach presents an efficient and robust solution by integrating edges and regions. First, a region segmentation method is applied to obtain the approximate shape of the building. Second, Hough transformation is employed to derive the two perpendicular line sets corresponding to the building boundary. Third, a subset of the intersectional nodes of the two line sets is utilized to construct a building structural graph, based on the analysis of grey value difference between the two sides of each line segment. Finally, a graph search algorithm is performed to retrieve all the cycles in the structural graph. The cycle corresponding to the building boundary is identified as the final building outline on the basis of its area. Two experiments were carried out to evaluate and validate this approach and experimental results confirm its effectiveness and robustness.