Binocular vision is a classical and efficient method in machine vision. Aiming at the problem that it is difficult to extract feature points of smooth surfaces without chromatic aberration, we propose a method of creating color features on surfaces with uniform laser grids, and a feature point extraction and matching algorithm. Firstly, in order to extract the laser grid line, the laser line breakpoint is spliced and transformed into a single pixel connected line by the expansion and corrosion algorithm. Then, the feature points are extracted by the connectivity of eight neighborhood and four neighborhood of points on the connected line. Finally, the extracted feature points are numbered according to the location information to complete the matching of feature points. The experimental results show that the algorithm has good robustness, high extraction accuracy, high matching accuracy and high repetition rate. The distance error between the feature points after three-dimensional reconstruction is less than 0.05 mm, and the standard deviation is 0.0362 mm. The proposed algorithm can carry out feature point extraction and matching directly, which is more accurate than the method of discrete feature lines as feature points. It can be applied to the uniform sampling detection of points on surfaces.