• Journal of Internet Computing and Services
• /
• v.9 no.1
• /
• pp.145-158
• /
• 2008

The detected arcs by the cone intersection(CI) method exist within a tolerant error from the original curve. But the position of breakpoint by the CI method is sensitive to the tolerant error. The deviation of breakpoint position makes ill effects to the detection of arc center or radius. In this paper a improved CI method for center detection and arc segmentation is proposed. The detected arcs from curves by the proposed method have very stable mean of deviations from the original curves. The experimental results show that the position of breakpoint by the proposed method is closer to real position than the one by other methods.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.713-718
• /
• 1994

Voronoi diagrams for closed shapes have many practical applications, ranging from numerical control machining to mesh generation. Shape offset based on Voronoi diagram avoids the topological problems encountered in traditional offsetting algorithms. In this paper, we propose a procedure for generating a Voronoi diagram and an exact offset for planar curve. A planer curve can be defined by free-form curve segements. The procedure consists of three steps : 1) segmentation by minimum curvature, 2) construction of Voronoi diagram, and 2) generation of the exact offset.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.430-433
• /
• 1996

The shape of an object plays a very important role in pattern analysis and classification. Roughly, the researches on this topic can be classified into three fields, i.e. (i) edge detection, (ii) dominant points extraction, and (iii) shape recognition and classification. Many works have been done in these three fields. However, it is very seldom to see the research that discusses the connection relationship of objects. This problem is very important in robot assembly systems. Therefore, here we focus on this problem and discuss how to recover the connection relationship of planar objects. Our method is based on the partial curve identification algorithm. The experiment results show the efficiency and validity of this method.