A Building Extraction Method via Gabor Filter and Multi-Orientation pi Local Binary Pattern Operator

As buildings constitute the main component of urban areas, which can provide several kinds of information. In this paper, a building extraction method based on the high resolution remote sensing image via Gabor filter and multi-orientation pi local binary pattern (LBP) operator is proposed to aim at the application requirements of rapid, accurate urban planning and visual management. At first, the multi-dimensional texture features are extracted by using Gabor filter for the original image. Further, some training samples are obtained by multi-orientation pi LBP operator at different orientations. Finally, the pixel-level discrimination is conducted for texture features, and achieves the location and shape of buildings. Experimental results demonstrate that the overall extraction accuracy has reached 94%, and the extracted results coincide with the distribution of each building, the proposed method is accurate to complete the task of building extraction, and has an excellent applicability for land management.