Abstract
Three-dimensional reconstruction of cochlear model is commonly used to measure the cochlear contour of patients with high accuracy and configure appropriate hearing aids. To improve the matching accuracy of 3D reconstruction of cochlear model, a triple screening point cloud registration method based on image and geometric features is proposed in this paper. Firstly, extracting the image feature points by SIFT algorithm, then eliminating the mismatched point pairs according to the RANSAC algorithm. Secondly, the average value of the normal feature is introduced to select the feature points with obvious geometric feature region. Thirdly, based on the point cloud fast point feature histogram (FPFH), the matching feature point pairs with image features and geometric features are selected to complete the coarse registration. Finally, iterative closest point (ICP) algorithm is used to achieve fine registration. The proposed algorithm is more comprehensive and effective for finding feature points then ensures the accuracy of registration results. In addition, results of the simulation show that the proposed algorithm reduces both the matching error and the total number of iterations compared with some existing algorithms.
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