A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part...A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part,curvature scale space is applied to multi-scale analysis and original feature detection. To obtain the primary and secondary curve primitives,feature fusion is realized by multi-scale feature detection information transmission. In the second part: projection height function is presented based on the area of quadrilateral,which improved criterions of sectional curve feature classification. Results of synthetic curves and practical scanned sectional curves are given to illustrate the efficiency of the proposed algorithm on feature extraction. The consistence between feature extraction based on multi-scale curvature analysis and curve primitives is verified.展开更多
基金Supported by the Natural Science Foundation of China (50175063)
文摘A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part,curvature scale space is applied to multi-scale analysis and original feature detection. To obtain the primary and secondary curve primitives,feature fusion is realized by multi-scale feature detection information transmission. In the second part: projection height function is presented based on the area of quadrilateral,which improved criterions of sectional curve feature classification. Results of synthetic curves and practical scanned sectional curves are given to illustrate the efficiency of the proposed algorithm on feature extraction. The consistence between feature extraction based on multi-scale curvature analysis and curve primitives is verified.