计算机工程与应用2018，Vol.54Issue(7)：196-200,5.DOI:10.3778/j.issn.1002-8331.1611-0332
基于改进HOG特征的建筑物识别方法
Building recognition method based on improved HOG feature
摘要
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 charac-teristics 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 perfor-mance than the steerable filtered-based building recognition method,and it is proven that the proposed method can effec-tively identify buildings.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Key words
building recognition/histogram of oriented gradients/feature extraction/steerable filters/support vector machine分类
信息技术与安全科学引用本文复制引用
杨松,李盛阳,邵雨阳,郑贺..基于改进HOG特征的建筑物识别方法[J].计算机工程与应用,2018,54(7):196-200,5.基金项目
中国科学院空间科学研究院培育项目(No.Y5031211WY). （No.Y5031211WY）
