In order to solve the problems with the traditional 3D model registration methods, such as the higher requirements for the initial locations of the two point clouds and the lower accuracy of model registration sometimes, a 3D model registration method based on SURF feature extraction of the two 3D model projection images is proposed. Firstly, the range of the projection image is determined by the 3D model data, and the model grid which each projection image pixel belongs to is deduced. Thus the two-dimensional projection image can be calculated by the mapping relationship from the projected image to the texture image. Then, the SURF feature points and the eigenvalues are calculated for the two projection images respectively. The feature matching is performed according to the SURF eigenvalues. Next, the feature point pairs in the two 3D models are extracted through the mapping relations between the 3D models' grid vertices and the projection image pixels. Finally, the two 3D model registration is implemented through the transformation matrix which is calculated from the matched feature point pairs in the two 3D models. The experimental results show that this method can improve the registration accuracy effectively and has good robustness under the condition of little change in registration time.%针对传统三维模型配准方法存在对点云初始位置有一定要求、模型配准的精度有时不高等问题,提出了一种基于三维模型投影图像SURF 特征提取的三维模型配准方法.首先通过扫描三维模型数据确定投影图像的范围,判断每个投影图像像素所隶属的模型网格,并求解从投影图像到纹理图像的映射关系,从而获取二维投影图像;然后对这两幅投影图像分别进行SURF 特征点的选取与特征值的计算,并按SURF 特征值进行特征匹配,再根据投影图像像素点与三维网格端点的映射关系计算三维特征点对;最后通过匹配的特征点对求取模型变换矩阵完成三维模型的配准.实验结果表明,该方法在配准时间变化不大的前提下,有效提高了配准精度,并具有较好的鲁棒性.
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