Building-Specific Recognition Algorithms Based on Image Sequence

Building extraction, recognition and corresponding three-dimensional modeling in image is an active research field, which is mainly applied to map feature extraction, urban population survey and so on. It has important significance in military and civil areas. Aiming at the shortcoming of the classical invariant feature extraction algorithm, a building recognition algorithm based on local feature and shape contour matching is proposed. Firstly, according to the fact that the whole building is susceptible to rotation and inclination, the local feature points of known buildings are extracted, and their orientation, position and angle are determined. At the same time, the similarity criterion and mapping function of arbitrary shape contour matching are formulated according to the scale change information of buildings in different states, and the building recognition under different illumination and scales is realized. The simulation results show that the method can quickly and accurately adapt to the construction in different environments. The accuracy of this method fluctuates around 97%, while the average accuracy of 20 experiments is 96.56%. The average accuracy of the SFBR method is 94.66%. Compared with the SFBR and SIFT methods, the average accuracy of the method is improved by nearly 2%.