Obtaining the type of a building automatically is significant for 3D modeling and image retrieval

but it is very difficult. In this paper

a new automatic urban building classification algorithm is proposed. This work analyzes the corner characteristic of common city buildings

applies morphological sieves of large scale to obtain rough contours. Then it uses a new segment and corner optimization process to count all kinds of corners

and realizes the automatic distinguish of flat roof buildings and non-flat buildings. The tests of dozens of images demonstrate the validity and effectiveness of the proposed segments optimization approach. The results indicate that it can achieve over 80% accuracy on type judgment with the presented method.