There are many phenomena that generate polygonal tessellations on surfaces of 3D objects. One interesting example is the jackfruit, a multiple fruit found in the tropics. A recent study found the best-fit spherical Vo...There are many phenomena that generate polygonal tessellations on surfaces of 3D objects. One interesting example is the jackfruit, a multiple fruit found in the tropics. A recent study found the best-fit spherical Voronoi diagram from a photo of jackfruit skin, but the optimization was relative to the radius of the sphere and the height of the spikes. In this study, we propose a method for adjusting the position of the center of the sphere in addition to these parameters. Experiments were conducted using both ideal and real data. However, convergence with real data has not been confirmed due to relaxation of the convergence condition.展开更多
3D shape searching is a problem of current interest in several different fields. Most techniques are developed for a particular domain and used to reduce a shape into a simpler shape representation. The techniques dev...3D shape searching is a problem of current interest in several different fields. Most techniques are developed for a particular domain and used to reduce a shape into a simpler shape representation. The techniques developed for a particular domain will also find application in other domains. We propose a new shape matching method. The SSRD (spherical sectioning railroad diagram) algorithm has the general shape distribution’s properties and overall features of the original model. The SSRD’s useful properties are discussed. We show the experimental results for the validity of our method.展开更多
The data processing technique and the method determining the optimal number of measured points are studied aiming at the sphericity error measured on a coordinate measurement machine （CMM）. The consummate criterion ...The data processing technique and the method determining the optimal number of measured points are studied aiming at the sphericity error measured on a coordinate measurement machine （CMM）. The consummate criterion for the minimum zone of spherical surface is analyzed first, and then an approximation technique searching for the minimum sphericity error from the form data is studied. In order to obtain the minimum zone of spherical surface, the radial separation is reduced gradually by moving the center of the concentric spheres along certain directions with certain steps. Therefore the algorithm is precise and efficient. After the appropriate mathematical model for the approximation technique is created, a data processing program is developed accordingly. By processing the metrical data with the developed program, the spherical errors are evaluated when different numbers of measured points are taken from the same sample, and then the corresponding scatter diagram and fit curve for the sample are graphically represented. The optimal number of measured points is determined through regression analysis. Experiment shows that both the data processing technique and the method for determining the optimal number of measured points are effective. On average, the obtained sphericity error is 5.78 μm smaller than the least square solution, whose accuracy is increased by 8.63%; The obtained optimal number of measured points is half of the number usually measured.展开更多
基金Partly Supported by the Grant-in-Aid for Basic Research of MEXT(No.24360039)
文摘There are many phenomena that generate polygonal tessellations on surfaces of 3D objects. One interesting example is the jackfruit, a multiple fruit found in the tropics. A recent study found the best-fit spherical Voronoi diagram from a photo of jackfruit skin, but the optimization was relative to the radius of the sphere and the height of the spikes. In this study, we propose a method for adjusting the position of the center of the sphere in addition to these parameters. Experiments were conducted using both ideal and real data. However, convergence with real data has not been confirmed due to relaxation of the convergence condition.
基金Project supported by the Basic Research Program of the Korea Science & Engineering Foundation (No. R01-2006-000-10327-0), and the Korea Research Foundation Grant funded by the Korean Gov-ernment (MOEHRD) (No. KRF-2005-041-D00903)
文摘3D shape searching is a problem of current interest in several different fields. Most techniques are developed for a particular domain and used to reduce a shape into a simpler shape representation. The techniques developed for a particular domain will also find application in other domains. We propose a new shape matching method. The SSRD (spherical sectioning railroad diagram) algorithm has the general shape distribution’s properties and overall features of the original model. The SSRD’s useful properties are discussed. We show the experimental results for the validity of our method.
基金This project is supported by National Natural Science Foundation of China (No.50475117)Municipal Science and Technology Commission of,Tianjin China(No.0431835116).
文摘The data processing technique and the method determining the optimal number of measured points are studied aiming at the sphericity error measured on a coordinate measurement machine （CMM）. The consummate criterion for the minimum zone of spherical surface is analyzed first, and then an approximation technique searching for the minimum sphericity error from the form data is studied. In order to obtain the minimum zone of spherical surface, the radial separation is reduced gradually by moving the center of the concentric spheres along certain directions with certain steps. Therefore the algorithm is precise and efficient. After the appropriate mathematical model for the approximation technique is created, a data processing program is developed accordingly. By processing the metrical data with the developed program, the spherical errors are evaluated when different numbers of measured points are taken from the same sample, and then the corresponding scatter diagram and fit curve for the sample are graphically represented. The optimal number of measured points is determined through regression analysis. Experiment shows that both the data processing technique and the method for determining the optimal number of measured points are effective. On average, the obtained sphericity error is 5.78 μm smaller than the least square solution, whose accuracy is increased by 8.63%; The obtained optimal number of measured points is half of the number usually measured.
