Structured light 3D measurement technology is increasingly utilized in various fields, including automated production and robotic vision. The performance of its core technology, laser center extraction, directly influences the efficiency and accuracy of structured light measurement. In this paper, we develop a laser center extraction algorithm on an FPGA-based image acquisition system and optimize and accelerate the algorithm through modular design and pipeline operations, leveraging the parallel processing capabilities of FPGA. To address the issue of noise interference in image processing systems, we propose an image preprocessing scheme based on Gaussian filtering. The development and optimization of this image preprocessing algorithm effectively eliminate noise and interference, thereby enhancing the accuracy and stability of the system. Utilizing the abundant logic resources of FPGA and its parallel processing efficiency, we successfully implement and parallelize the image preprocessing and laser center extraction algorithms. Experimental results demonstrate that the system can acquire and process 1280 × 864 images at a frame rate of 3500 Hz, extract center coordinates at a sub-pixel level in real time, and perform exceptionally well in terms of processing speed, accuracy, and stability.