Laser Stripe Center Extraction Based on Hessian Matrix and Regional Growth

The accurate and fast extraction of structured light stripe centers is a key problem in a three-dimensional (3D) measurement system. Aiming at the existing contradiction between extraction precision and speed of structured light stripe centers, a novel laser stripe center extraction method is proposed based on the Hessian matrix and the regional growth. First, the adaptive threshold method is used to extract the region of interest from the images, and the initial position of the pixel-level stripe center is determined by the maximum value of the gray value. Second, the sub-pixel-level strip center point in the normal direction of the initial point is obtained by the Hessian matrix. Finally, the strip center is used as a seed point for the regional growth iteration operation and thus the stripe center is accurately extracted. In the regional growth algorithm, the problem of a large number of Gaussian convolutional operations in the traditional method is solved, and the extraction speed of the stripe center is increased. The experimental results show that the stripe center extracted by the proposed algorithm has a high accuracy and the real-time online requirements of the 31) measurement system is satisfied. The mean square error (RMS) of this algorithm is reduced by 2.02 pixel compared with that of gray-gravity algorithm, and the extraction speed is 40 times higher than that of Steger algorithm.