3D measurement of structured light technology is an extremely vital approach to obtain 3D information of objects. Extraction of the centerline of laser stripe is a key factor that could affect the accuracy and speed of 3D measurement of structured light in the meantime. A method of extracting centerline of laser stripe for 3D measurement of structured light that adaptive to multiple scenarios was proposed. The adaptive convolution template was generated by making full use of the geometric information and correlation of laser stripe in the image, which can filter and enhance the image quality of laser stripe and enable the gray value of cross-section of laser stripe satisfy the Gauss distribution. The sub-pixel accurate localization and extraction of laser stripe centerline were realized by gray weighted algorithm. The experimental results show that the proposed adaptive convolutional algorithm can extract the laser stripe centerlines of the objects with different shapes and materials based on multi-scenarios and overcome the influence of uneven brightness and noise at the same time. Based on the algorithm, the extraction time of single frame is shortened to 0.107 s and the relative error is reduced to 0.076 5%, which improves the extraction accuracy and speed of laser stripe centerline effectively.