An open resection of liver tumors is the most effective method for their treatment. The intraoperative three-dimensional （3D） reconstruction of liver surface based on binocular structural light plays an important role in the accurate localization of liver tumors. However， due to factors such as illumination in the surgical environment and the location of images captured by the binocular camera， a local brightness saturation occurs in the captured images， leading to hindrance in the three-dimensional reconstruction of the liver surface. To solve this problem， an adaptive optimal fringe grating based on the segmentation projection algorithm of different reflectivity regions is proposed in this paper. First， a physical model and a sketch of illumination on the liver surface under binocular system were established， and the influence of local brightness saturation on the liver surface was analyzed. The region was then divided according to the different reflectivity of the liver surface. The intensity of the adaptive optimal fringe grating was calculated according to the region segmentation projection algorithm of different reflectivity， so as to achieve the partition projection of the liver surface. The saturation points of the left and right camera images were transferred to the streaks cast by the projector. The effectiveness of the proposed method to overcome the local brightness saturation of the liver surface was verified by the local brightness saturation experiment. Finally， the experimental results of porcine liver showed that the deletion rate of porcine liver 3D reconstruction surface decreased from 1.1%， 2.9%， and 1.4% to 0%， respectively， under three different operating conditions due to local brightness saturation， and the accuracy of porcine liver 3D reconstruction reached 0.75 mm. The method described in this paper can essentially meet the requirements of doctors， including the intraoperative 3D reconstruction accuracy of liver surface to be less than 1 mm with no defects in the reconstructed surface.