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董玉德, 宋忠辉, 陈进富, 鲍齐友, 张荣团, 白苏诚. 面向轮胎点云的胎面花纹边界特征提取[J]. 计算机辅助设计与图形学学报, 2017, 29(5): 939-949.
引用本文: 董玉德, 宋忠辉, 陈进富, 鲍齐友, 张荣团, 白苏诚. 面向轮胎点云的胎面花纹边界特征提取[J]. 计算机辅助设计与图形学学报, 2017, 29(5): 939-949.
Dong Yude, Song Zhonghui, Chen Jinfu, Bao Qiyou, Zhang Rongtuan, Bai Sucheng. Extraction of Boundary Features of Tread Patterns from Tire Point Cloud[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(5): 939-949.
Citation: Dong Yude, Song Zhonghui, Chen Jinfu, Bao Qiyou, Zhang Rongtuan, Bai Sucheng. Extraction of Boundary Features of Tread Patterns from Tire Point Cloud[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(5): 939-949.

面向轮胎点云的胎面花纹边界特征提取

Extraction of Boundary Features of Tread Patterns from Tire Point Cloud

  • 摘要: 为有效地从点云数据中提取吻合轮胎结构设计特征的花纹边界,提出面向胎面点云映射阵的花纹边界提取方法.首先以优化分割获取的胎面点云为对象,将栅格作为基本单元进行3D胎面点云到点云映射阵的转化;然后采用列链码连通性生长的方式获取花纹结构知识单元,构建能够表征花纹结构信息的结构知识库;最后通过求解知识单元相似度实现知识库中花纹的聚类,并借助模式识别实现聚类结果与花纹设计基本类型的匹配,进而驱动基本类型花纹边界特征归类机制实现花纹边界特征点的提取.实例结果表明,该方法能够高效、稳定、准确地提取半钢子午线轮胎点云中的花纹边界特征信息.

     

    Abstract: In order to effectively extract pattern borders consistent with tire structure design characteristics from point cloud data, an extraction method of tire pattern border based on the point cloud mapping matrix is proposed. Firstly, the tire tread point cloud acquired by optimizing segmentation is set as the object, and the grid is treated as the elementary unit, so as to realize the transformation from 3D tire tread point cloud into point cloud mapping matrix. Secondly, pattern structure knowledge unit is gained via the connective growth mode of column chain codes, and a structure knowledge base able to characterize pattern structure information is built. Then, pattern clustering in the knowledge base is realized by calculating the similarity of knowledge units, and matching between clustering results and the basic pattern design types is realized via pattern recognition. Finally, pattern border characteristic points are extracted with the classification mechanism of basic pattern border characteristics. The illustrative results indicate that this method can extract pattern border characteristics in semi-steel radial tire point cloud efficiently, stably and accurately.

     

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