Transactions of Nanjing University of Aeronautics & Astronautics
A Sequence Image Matching Method Based on Improved High-Dimensional Combined Features
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Abstract:
Image matching technology is theoretically significant and practically promising in the field of autonomous navigation. Addressing shortcomings of existing image matching navigation technologies, the concept of high-dimensional combined feature is presented based on sequence image matching navigation. To balance between the distribution of high-dimensional combined features and the shortcomings of the only use of geometric relations, we propose a method based on Delaunay triangulation to improve the feature, and add the regional characteristics of the features together with their geometric characteristics. Finally, k-nearest neighbor (KNN) algorithm is adopted to optimize searching process. Simulation results show that the matching can be realized at the rotation angle of -8° to 8° and the scale factor of 0.9 to 1.1, and when the image size is 160 pixel×160 pixel, the matching time is less than 0.5 s. Therefore, the proposed algorithm can substantially reduce computational complexity, improve the matching speed, and exhibit robustness to the rotation and scale changes.
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Project Supported:
This work was supported by the National Natural Science Foundations of China (Nos.51205193, 51475221).
Clc Number:
TN967.2
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