A Fast Image Matching Algorithm Using a Combination of Line Segment Features

结合线段组合特征的快速图像匹配算法

The scene matching navigation is a research focus in the field of autonomous navigation,but the real-time performance of image matching algorithm is difficult to meet the needs of real navigation systems.Therefore,this paper proposes a fast image matching algorithm.The algorithm improves the traditional line segment extraction algorithm and combines with the Delaunay triangulation method.By combining the geometric features of points and lines,the image feature redundancy is reduced.Then,the error with confidence criterion is analyzed and the matching process is completed.The simulation results show that the proposed algorithm can still work within 3°rotation and small scale variation.In addition,the matching time is less than 0.5 s when the image size is 256 pixel×256 pixel.The proposed algorithm is suitable for autonomous navigation systems with multiple feature distribution and higher real-time requirements.

图像匹配导航技术是近年来自主导航领域的研究热点之一,但图像匹配算法的实时性却难以满足现实导航系统的需求。本文改进了传统线段提取算法,并引入了Delaunay三角剖分法,通过结合点线几何特征,减少了图像特征冗余。结合置信度准则对误差进行分析,完成匹配过程。仿真结果表明,本文算法在3°旋转并有尺度变化的情况下仍然能完成匹配,图像尺寸为256像素×256像素时匹配时间在0.5 s以内,适用于特征分布较多且实时性要求较高的自主导航系统。