融合CANNY算子与HOG算子的建筑物识别方法

Building Recognition Method Combining CANNY Operator and HOG Operator

建筑物由于其多样性和所处环境的复杂性成为了计算机视觉领域研究的热点。针对当下识别建筑物的方法准确率不高的问题,提出了融合CANNY算子与HOG算子的方法识别建筑物。利用CANNY边缘检测算子提取建筑物的边缘信息,之后对边缘检测后的建筑物图像使用HOG算子提取其边缘轮廓特征,构造特征向量,将其输入非线性支持向量机(SVM)中进行分类。通过在Sheffield建筑物数据集中进行验证,其识别准确率可以达到97%以上。实验结果表明,提出的方法在识别建筑物的鲁棒性及准确度等方面具有相对较好的效果。

Buildings have become a hotspot in the field of computer vision research due to their diversity and the complexity of the environment.Aiming at the problem of low accuracy of the current method of identifying buildings,in this paper,a method of combining CANNY operator and HOG operator is proposed to identify the building.CANNY edge detection operator is used to extract the edge information of the building;and then HOG operator is used to extract the edge contour feature of the building image after the edge detection,construct the feature vector,and input it into the nonlinear support vector machine(SVM)for classification.Through verification in the Sheffield building data set,its recognition accuracy can reach more than 97%.The experimental results show that the method proposed in this paper has a relatively good effect in the robustness and accuracy of recognizing buildings.