Deep Learning Prediction Frame Matching Algorithm of Small Celestial Navigation Landmarks

Abstract

Deep learning algorithm has a higher recognition rate for navigation landmarks such as small meteor craters than traditional algorithms，but it is difficult to achieve matching under various image changes. To solve this problem，a description method of recognition prediction box based on feature descriptor was proposed，and the matching of recognition results was completed. Firstly，the circular support region of the recognition prediction frame was determined and a 10-dimensional feature descriptor with rotation and translation scale and luminance invariance was constructed and the prediction frame was matched by the relative distance between descriptor vectors. The results show that the proposed algorithm is robust to images under different transformations，and the correct matching rate of the prediction frame is over 90%. It may provide the reference for the asteroid exploration navigation system.

Keywords

deep learning / navigation landmarks / support area / feature descriptor / prediction frame matching