Similarity Measures of Sectional Contour based Surface Feature Eztraction From Point Clouds

摘要：

Surface feature extraction from point clouds is an important technology of 3D digital geometric signal understanding. The existing surface feature extraction methods have limit of precision while segmenting point clouds from complex surfaces with open contours, branching and blending features. A new practical method is presented for surface feature extraction based on similarity measures of sectional contour. The shape description of arc length and rotation angle is discussed. The similarity of feature is determined according to the normalized cross correlation coefficient of sectional contour feature point clouds. Branch, blend, dissimilarity and precise feature point are distinguished based on the similarity measures of sectional contour feature point. Surface feature is automatically extraction by feature points of point clouds. Experiments show that the proposed surface extraction method can accurately segment the complex surface with open contour, branching and blending feature. Complex surface is segmented into individual surfaces according to similarity measure rules, reflecting the original design intent.

关键词： surface eztraction sectional feature similarity measures reverse engineering

作者: Hongjuan Yang Jiwen Chen Yiqi Zhou

作者单位: School of Electrical and Information Engineering,Shan dong jian zhu University,Jinan 250061 School of Mechanical and Electrical Engineering,Shan dong jian zhu University,Jinan 250101 School of Mechanical Engineering,Shandong University,Jinan 250061

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3462-3465

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）