Local Feature Extraction Algorithm of Human Body Scanning Data

Segmentation and extraction of the target feature points from the unregistered,noisy data set of human body scanning and measuring are discussed.We have fitted the noise scanned data line with KS principal curve,which is based on the K-means theory.The crossing zero of curvature was used to segment and estimate the position of target feature points.And optimization scheme named variable fuzzy partition is also presented to improve the searching for local feature area.