Feature extraction and matching for autonomous navigation based on Fourier descriptors

Autonomous navigation is a key part for soft-landing asteroid,and the technology of feature recognition and matching is critical in this part. Some approaches were discussed in this paper. First, we use two-dimensional maximum entropy thresholding segmentation for extraction the extract features, and then apply Fourier descriptors for feature matching. Combing Fourier discriptiors with PCA, and with the help of vector relationship of features, we conduct a series of feature matching experiments. The experimental results show that this method can extract and match features effectively.