Application of Adaptive Combined Filtering Algorithm in 3D Artificial Limb Model
Aiming at the problems that the classical statistical filtering algorithm can't adap-tively select parameters and the traditional bilateral filtering algorithm can't consider both feature preservation and smoothness,an adaptive combined filtering algorithm is proposed.Firstly,the adaptive standard deviation multiple based on local point cloud volume is intro-duced to flexibly filter out the large-scale noise of prosthetic point cloud;On the basis of fil-tering out large-scale noise,a new covariance matrix weighting method is introduced to im-prove the accuracy of estimating the normal direction of point cloud,and the feature weight factor is improved by the mean value of the degree of change of the included angle in the nor-mal direction,so as to enhance the conservation characteristics of the bilateral filter factor,aiming at smoothing the small-scale noise of the three-dimensional prosthetic model.Com-pared with statistical filtering and bilateral filtering alone,the maximum error of the pro-posed algorithm in the three prosthetic models is reduced by at least 5%;The average error is reduced by at least 6.9%.The simulation results show that the improved algorithm can effectively eliminate the large-scale noise of the prosthetic model while avoiding the over smoothness and incomplete noise removal,and can better maintain the geometric features in the model.
万方数据
维普
