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Applying Rational Envelope curves for skinning purposes
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作者 Kinga KRUPPA 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2021年第2期202-209,共8页
Special curves in the Minkowski space such as Minkowski Pythagorean hodograph curves play an important role in computer-aided geometric design,and their usages are thoroughly studied in recent years.Bizzarri et al.(20... Special curves in the Minkowski space such as Minkowski Pythagorean hodograph curves play an important role in computer-aided geometric design,and their usages are thoroughly studied in recent years.Bizzarri et al.(2016)introduced the class of Rational Envelope(RE)curves,and an interpolation method for G1 Hermite data was presented,where the resulting RE curve yielded a rational boundary for the represented domain.We now propose a new application area for RE curves:skinning of a discrete set of input circles.We show that if we do not choose the Hermite data correctly for interpolation,then the resulting RE curves are not suitable for skinning.We introduce a novel approach so that the obtained envelope curves touch each circle at previously defined points of contact.Thus,we overcome those problematic scenarios in which the location of touching points would not be appropriate for skinning purposes.A significant advantage of our proposed method lies in the efficiency of trimming offsets of boundaries,which is highly beneficial in computer numerical control machining. 展开更多
关键词 medial axis transform ENVELOPE INTERPOLATION SKINNING Circle
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Shape Recognition and Retrieval Based on Edit Distance and Dynamic Programming
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作者 潘鸿飞 梁栋 +2 位作者 唐俊 王年 李薇 《Tsinghua Science and Technology》 SCIE EI CAS 2009年第6期739-745,共7页
An important aim in pattern recognition is to cluster the given shapes. This paper presents a shape recognition and retrieval algorithm. The algorithm first extracts the skeletal features using the medial axis transfo... An important aim in pattern recognition is to cluster the given shapes. This paper presents a shape recognition and retrieval algorithm. The algorithm first extracts the skeletal features using the medial axis transform. Then, the features are transformed into a string of symbols with the similarity among those symbols computed based on the edit distance. Finally, the shapes are identified using dynamic programming. Two public datasets are analyzed to demonstrate that the present approach is better than previous approaches. 展开更多
关键词 skeletal features medial axis transform edit distance dynamic programming
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