A principal direction Gaussian image （PDGI）-based algorithm is proposed to extract the regular swept surface from point cloud. Firstly, the PDGI of the regular swept surface is constructed from point cloud, then the...A principal direction Gaussian image （PDGI）-based algorithm is proposed to extract the regular swept surface from point cloud. Firstly, the PDGI of the regular swept surface is constructed from point cloud, then the bounding box of the Gaussian sphere is uniformly partitioned into a number of small cubes （3D grids） and the PDGI points on the Gaussian sphere are associated with the corresponding 3D grids. Secondly, cluster analysis technique is used to sort out a group of 3D grids containing more PDGI points among the 3D grids. By the connected-region growing algorithm, the congregation point or the great circle is detected from the 3D grids. Thus the translational direction is determined by the congregation point and the direction of the rotational axis is determined by the great circle. In addition, the positional point of the rotational axis is obtained by the intersection of all the projected normal lines of the rotational surface on the plane being perpendicular to the estimated direction of the rotational axis. Finally, a pattem search method is applied to optimize the translational direction and the rotational axis. Some experiments are used to illustrate the feasibility of the above algorithm.展开更多
Based on the analysis of the unique shapes and writing styles of Uyghur characters,we design a framework for prototype character recognition system and carry out a systematic theoretical and experimental research on i...Based on the analysis of the unique shapes and writing styles of Uyghur characters,we design a framework for prototype character recognition system and carry out a systematic theoretical and experimental research on its modules.In the preprocessing procedure,we use the linear and nonlinear normalization based on dot density method.Both structural and statistical features are extracted due to the fact that there are some very similar characters in Uyghur literature.In clustering analysis,we adopt the dynamic clustering algorithm based on the minimum spanning tree（MST）,and use the k-nearest neighbor matching classification as classifier.The testing results of prototype system show that the recognition rates for characters of the four different types（independent,suffix,intermediate,and initial type） are 74.67%,70.42%,63.33%,and 72.02%,respectively;the recognition rates for the case of five candidates for those characters are 94.34%,94.19%,93.15%,and 95.86%,respectively.The ideas and methods used in this paper have some commonality and usefulness for the recognition of other characters that belong to Altaic languages family.展开更多
基金This project is supported by Key Program of National Natural Science Foundation of China(No.50435020).
文摘A principal direction Gaussian image （PDGI）-based algorithm is proposed to extract the regular swept surface from point cloud. Firstly, the PDGI of the regular swept surface is constructed from point cloud, then the bounding box of the Gaussian sphere is uniformly partitioned into a number of small cubes （3D grids） and the PDGI points on the Gaussian sphere are associated with the corresponding 3D grids. Secondly, cluster analysis technique is used to sort out a group of 3D grids containing more PDGI points among the 3D grids. By the connected-region growing algorithm, the congregation point or the great circle is detected from the 3D grids. Thus the translational direction is determined by the congregation point and the direction of the rotational axis is determined by the great circle. In addition, the positional point of the rotational axis is obtained by the intersection of all the projected normal lines of the rotational surface on the plane being perpendicular to the estimated direction of the rotational axis. Finally, a pattem search method is applied to optimize the translational direction and the rotational axis. Some experiments are used to illustrate the feasibility of the above algorithm.
基金Supported by the National Natural Science Foundation of China (61065001)
文摘Based on the analysis of the unique shapes and writing styles of Uyghur characters,we design a framework for prototype character recognition system and carry out a systematic theoretical and experimental research on its modules.In the preprocessing procedure,we use the linear and nonlinear normalization based on dot density method.Both structural and statistical features are extracted due to the fact that there are some very similar characters in Uyghur literature.In clustering analysis,we adopt the dynamic clustering algorithm based on the minimum spanning tree（MST）,and use the k-nearest neighbor matching classification as classifier.The testing results of prototype system show that the recognition rates for characters of the four different types（independent,suffix,intermediate,and initial type） are 74.67%,70.42%,63.33%,and 72.02%,respectively;the recognition rates for the case of five candidates for those characters are 94.34%,94.19%,93.15%,and 95.86%,respectively.The ideas and methods used in this paper have some commonality and usefulness for the recognition of other characters that belong to Altaic languages family.
