During camera calibration process based on a circular calibration board, when the lens distortion is large, the image quality decreases, and the circular projection edge becomes blurry, resulting in calibration errors. Accordingly, a high-precision camera technique based on subpixel edge detection and center correction compensation is proposed. First, the Canny-Zernike moment method was used to extract subpixel-level circular feature contour points. Moreover, edge point chains were used to connect independent contour points to obtain closed-loop accurate feature contours, enhancing the ability to extract fuzzy edge contours. Second, the inner and outer contours were sampled separately, and points were taken to fit the ellipse. The mean of the two centers was used as the feature points, and an ordered feature point set was obtained through the three-point judgment sorting method for rough calibration. Finally, the rough calibration parameters were used to calibrate the sampling point set of the contour, and the center coordinates were reobtained before backprojection onto the image for precise camera calibration, achieving center correction compensation calibration under distortion. The experimental results show that the proposed method effectively improves the accuracy of camera calibration when the lens distortion is large.