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Unit panel nodes detection by CNN on FAST reflector

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arxiv 1909.11806 v1 pith:FSBSEIUF submitted 2019-09-25 astro-ph.IM eess.IV

Zhi-Song Zhang , Li-Chun Zhu , Wei Tang , Xin-Yi Li This is my paper · ORCID
classification astro-ph.IMeess.IV
keywords nodesreflectordetectdetectionfastphotogrammetryphotosrate
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The 500-meter Aperture Spherical Radio Telescope(FAST) has an active reflector. During the observation, the reflector will be deformed into a paraboloid of 300-meters. To improve its surface accuracy, we propose a scheme for photogrammetry to measure the positions of 2226 nodes on the reflector. And the way to detect the nodes in the photos is the key problem in photogrammetry. This paper applies Convolutional Neural Network(CNN) with candidate regions to detect the nodes in the photos. The experiment results show a high recognition rate of 91.5%, which is much higher than the recognition rate of traditional edge detection.

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