Abstract

In order to solve the problem of selecting lunar soft landing spot, this study doped out a solution to the problem. Collect images of the lunar surface and analyze them. According to the fact that the speed and accuracy of selecting lunar soft landing spot are highly required in the field of aviation, this study proposed circle pit recognition method based on Multi-level de-noising Hough transform. In this method, do halved sampling process repeatedly on the original images in order to get a set of variable resolution image of pyramid like. Search the circle pit position in the lowest resolution image roughly. And then refine soft landing point in the high resolution images in order to get the lunar circle pit position accurately. Do experiments using the images of the lunar surface which were collected by Chang 'e-3. What’s more, selecting the appropriate landing point selection mechanism to select a soft landing point and verify results. After doing all of these, compare this method with five kinds of traditional methods. The experimental results shows the method which is proposed in this study effectively improves the speed and accuracy of Hough transform circle detection, with strong robustness and high efficiency, so as to improve the speed and accuracy of selected lunar soft landing point.

Keywords:

Circle pit recognition, halved sampling, lunar soft landing point, multi-level de-noising hough transform,

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Competing interests

The authors have no competing interests.

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