In order to solve the problem that the traditional stripe center extraction algorithm is sensitive to material and noise, an adaptive structured light stripe center extraction algorithm was used to extract the fringe sub-pixel coordinates. The algorithm first preprocesses the image, extracts the region of interest of the stripe image by using the image mask operation, eliminates noise interference through the adaptive convolution template, and obtains the pixel sets of the stripe area cross-sectional width and center coordinates. Secondly, according to the pixel set of the central coordinates, the initial coordinate value of the stripe center was calculated by the quadratic weighted gray centroid method, which will be used as the seed point for regional growth operation, then combined with principal component analysis to decompose the characteristic matrix, and finally the sub-pixel coordinate point of the center of the linear structured light was obtained. The results show that the center sub-pixel coordinates of the structured light stripe can be effectively and quickly obtained by this algorithm. Compared with the gray-scale barycenter method, the extraction results of the algorithm in this paper are less volatile and have a relatively small standard error. The extraction speed is nearly 4 times higher than that of the Steger method based on Hessian matrix, which meets the real-time requirements of the industrial measurement system. The proposed algorithm in this paper has high extraction accuracy, good robustness, low computational complexity, and high real-time performance, which provides nice accuracy guarantee for the subsequent 3-D vision measurement system.