A Fast Image Matching Algorithm Based on Yolov3

基于Yolov3神经网络的快速图像精匹配算法

In view of the fact that the traditional Hausdorff image matching algorithm is very sensitive to the image size as well as the unsatisfactory real-time performance in practical applications,an image matching algorithm is proposed based on the combination of Yolov3.Firstly,the features of the reference image are selected for pretraining,and then the training results are used to extract the features of the real images before the coordinates of the center points of the feature area are used to complete the coarse matching.Finally,the Hausdorff algorithm is used to complete the fine image matching.Experiments show that the proposed algorithm significantly improves the speed and accuracy of image matching.Also,it is robust to rotation changes.

针对传统的Hausdorff图像匹配算法对于图像尺寸十分敏感、在实际应用中实时性不强的问题,提出一种结合Yolov3神经网络的图像匹配算法。首先,选取参考图像中的特征进行预训练;然后,利用训练结果对实测图像进行特征提取,利用特征区域的中心点坐标完成粗匹配;最后,对参考图与实测图的特征区域进行截取,利用Hausdorff算法完成图像的精匹配。实验结果表明,本文提出的算法显著提高了运算速度及匹配准确率,并且对旋转变化具有一定的鲁棒性。