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,thi...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.展开更多
基金supported by the Fundation of Graduate Innovation Center in Nanjing University of Aeronautics and Astronautics (No.kfjj20191506)
文摘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.
