关键词: 建筑物识别, 梯度方向直方图, 特征提取, 方向可控滤波器, 支持向量机

Abstract: With the development and the extensive application of machine learning methods, the building recognition technology is developed rapidly. For the building recognition, the recognition accuracy is still the focus of attention. The traditional gradient method of Histogram of Oriented Gradients（HOG） can not effectively describe the boundary characteristics of the building and it directly affects recognition result. The HOG method based on the steerable filters is proposed, and Support Vector Machine（SVM） is used as the training method. The experimental result is analyzed according to the average accuracy rate, TP, FP, Recall, Precision and F1. The results show that the proposed method has better performance than the steerable filtered-based building recognition method, and it is proven that the proposed method can effectively identify buildings.

Key words: building recognition, histogram of oriented gradients, feature extraction, steerable filters, support vector machine