This paper presents a new algorithm for center extraction of line structured light. Traditional segmentation algorithms often suffer from issues such as holes, discontinuity, and inaccuracy in image segmentation. To address these limitations, the EAST deep learning model is employed to accurately and efficiently extract the region of interest of laser stripes. This approach mitigates the susceptibility of traditional algorithms to noise interference and improves segmentation efficiency. In addition, the gray barycenter method is used to initially extract the detected effective light strip area, and finally the optimization algorithm is used to perform secondary optimization on the initial center line to realize the accurate extraction of the sub-pixel coordinates of the light strip center. The results show that the algorithm can more accurately extract the center of the line-structured light strip, which ensures the accuracy and stability of the strip center extraction.