To address the performance bottlenecks in real-time capability, accuracy, and noise robustness associated with multi-spot centroid extraction in complex industrial visual measurement scenarios, a fast and high-precision multi-spot centroid extraction method suitable for implementation on field-programmable gate array（FPGA） is proposed. The method integrates template matching, run-length-encoding–based connected-component identification, and a distance-weighted grayscale centroid technique to construct a multi-level collaborative optimization framework. Local grayscale statistics are exploited to achieve adaptive threshold segmentation and edge-noise suppression, thereby enhancing localization stability and computational parallelism. First, coarse spot localization is performed through local grayscale statistics and Gaussian-template cross-correlation, followed by dynamic generation of adaptive thresholds to improve the reliability of spot-region segmentation. Subsequently, a run-length-encoding connected-component structure is designed, which completes region labeling and coarse centroid estimation using only a single-line buffer, effectively reducing on-chip memory consumption. Finally, a distance-weighted grayscale centroid model is developed to improve localization accuracy and robustness under boundary blur and low signal-to-noise ratio conditions. Experimental results demonstrate that, under various spot distortions, noise distributions, and observation distances, the proposed method significantly outperforms traditional grayscale centroid and Gaussian-fitting approaches in terms of localization accuracy and error stability, reducing localization error by approximately 70% and improving robustness metrics by more than 50%. Within a measurement range of 10~30 m, the repeatability of centroid localization is better than 0.02 pixels, and the end-to-end system processing latency is reduced by approximately 89%. With its high accuracy, strong robustness, and low latency, the proposed method is well suited for real-time multi-spot detection in long-range industrial visual measurement applications and provides an effective technical solution for high-performance industrial measurement systems.