图像特征匹配是图像信息处理领域中极其重要的一项技术,目前已广泛应用于图像拼接、三维重建和视觉运动计算等领域。针对图像特征匹配中匹配准确性低的问题,提出一种能够更好适应动态场景和重复纹理的惯性导航辅助图像进行特征点匹配的方法。该方法首先提取前后两帧图像的ORB(Oriented FAST and Rotated BRIEF)特征;然后利用惯性测量单元的测量数据解算相机的运动,并计算第一帧图像中的特征点在第二帧图像中可能出现的区域;最后将第一帧图像中的特征点和与其对应的第二帧图像的可能区域中的特征点进行匹配,得到两帧图像的特征点匹配结果。实验结果表明,该方法的匹配准确率可以达到92%,能够显著提高图像特征匹配的准确性。

Image feature matching plays an essential role in the field of image information processing, which has been commonly used in image mosaic, three-dimensional reconstruction, visual motion calculation, and other related fields. In order to increase the matching accuracy of image feature matching, an image feature point matching method based on inertial navigation is proposed to be better adapted to the cases of dynamic scene and repeated texture. To begin with, the ORB(Oriented FAST and Rotated BRIEF) features is extracted from the first and second frames. After that, the data of the inertial measurement unit is used to decide the motion of the camera and also to locate where the feature points in the first frame may appear in the second frame. Finally, the matching result of the first two frames is obtained by matching the corresponding feature points in the first and second frames. The experimental results demonstrate that the matching accuracy of this method can reach up to 92%, which has significantly improve the accuracy of image feature matching.