As research and development in the field of machine vision continue to advance, the requirements for image processing have become more complex and diverse. Edge information detection is particularly important when processing real-time images. This paper designs an FPGA image edge detection system based on the Sobel algorithm, capable of real-time video image acquisition, processing, and display. Adaptive threshold and non-maximum suppression algorithms are used, combined with an 8-direction Sobel edge detection algorithm to improve detection accuracy. The Sobel edge detection algorithm is validated and implemented in hardware before and after improvement. A pipeline design is adopted to generate a sliding window to accelerate image processing and enhance the real-time performance of image processing. Hardware synthesis experiments show that the FPGA image edge detection system based on the Sobel algorithm can efficiently achieve image edge detection of video streams, improving image processing speed by 57%, providing comprehensive edge detail detection, enhancing video image processing efficiency, and can be used for target recognition and tracking research.