In the closed-loop fiber positioning control mode of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), stringent requirement is needed for time efficiency. Due to the high-resolution image required for fiber positioning and the impact of image transmission, there is still room for improvement in the current closed-loop control's time efficiency. The total time required for all fiber positioner to complete a positioning must be less than 5 minutes. To address this problem, this paper proposes an improved fiber position high-precision detection method based on FPGA (Field-Programmable Gate Array), which can fully utilize the computational resources of the edge hardware platform for image processing and significantly save the time required for computing high-resolution images. This paper compares the impact of several threshold algorithms on the centroid algorithm and uses Vivado HLS to port the algorithm to the FPGA. By labeling the spots, the centroid coordinates of the spots can be obtained in a single scan image. The results show that the FPGA-based centroid algorithm can effectively reduce the image processing time, and the improved centroid algorithm is more suitable for running on the FPGA. The algorithm has been experimentally verified and has been preliminarily applied to the closed-loop detection system of LAMOST. In the future, it can be further optimized and applied to the closed-loop detection system for multiple accumulations to improve detection accuracy, as well as to the next-generation multi-object astronomical telescope detection system with tens of thousands of fiber position detections.
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