Skull model feature point automatic calibration method

The invention discloses a skull model feature point automatic calibration method, relating to the technical field of image processing. The method includes, calculating the two-dimensional depth image by using a scale invariant feature transform (SIFT) algorithm; obtaining an initial feature point set of the reference skull model; calculating the two-dimensional depth image by using a scale invariant feature transform (SIFT) algorithm; the method comprises the steps of obtaining an initial feature point set of a reference skull model according to the skull model feature point set, filtering a candidate feature point set by using an E2LSH algorithm, generating a target feature point set, and mapping the target feature point set to the to-be-restored skull model, thereby realizing automatic calibration of skull model feature points, and improving the efficiency and accuracy of feature point automatic calibration. 本发明公开的颅骨模型特征点自动标定方法，涉及图像处理技术领域，利用尺度不变特征变换SIFT算法对二维深度图像进行计算，得到参考颅骨模型的初始特征点集，利用尺度不变特征变换SIFT算法对二维深度图像进行