提出一种对无规则点云进行三角网格重构的区域增长算法。
A region - growing algorithm was proposed to reconstruct triangular meshes unorganized point cloud.
提出一种新的由点云数据生成三角网格曲面的区域增长算法。
A new region-growing algorithm is presented for triangular mesh surface reconstruction from point-cloud data.
为了提取局部感兴趣区域，给出了一种基于灰度层共现矩阵的区域增长算法，分割出病灶区域，再结合迭代阈值算法进行病灶边界的磨合。
It presents a new region growing algorithm with gray level co-occurrence matrix to extract the focus region, the threshold segmentation is applied to improve the edge of segmented region.
为克服经典区域增长算法中门限选择困难、分割稳定性不高与串行处理速度慢的不足，提出了基于区域进化的快速区域增长图像分割算法。
To overcome the difficulty of manual threshold selection and slow speed of conventional region growing image segmentation algorithm, a region evolution image segmentation algorithm is proposed.
论文阐述了一种基于在线学习算法的彩色图像区域增长法，用于解决基于内容的图像检索系统。
This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.
提出了一种基于小区域增长的分割算法对人体肝脏的MDCT医学图像进行分割。
A segmenting algorithm for the human liver MDCT medical images based on small region growing is presented.
针对基于区域增长的图像分割方法，讨论和研究了其数据并行实现方法，证明了这种数据并行方法的正确性，并简要对算法性能进行了分析。
This paper discusses the data parallel algorithm and its implementation on region growing image segmentation, the correctness is proved, and the performance is also analyzed.
提出了一种基于区域增长和改进分水岭算法的胃腺癌细胞图像分割方法。
This paper presents a new kind of algorithm for cell image segmentation, which is based on region-growing and watersheds.
为了提高航空发动机管路测量数据的反求建模效率，提出了一种区域增长分割算法。
To improve the reverse modeling efficiency of aeroengine pipelines, a region-growing segmentation algorithm for aeroengine pipeline point cloud data is proposed based on geometric attributes.
该文主要讨论了基于区域增长的匹配算法中存在的问题，并对此算法进行了改进。
The dense matching algorithm has shown its advantage in this aspect. The thesis mainly discussed the problems of region-growth algorithm and made some improvements.
该文主要讨论了基于区域增长的匹配算法中存在的问题，并对此算法进行了改进。
The dense matching algorithm has shown its advantage in this aspect. The thesis mainly discussed the problems of region-growth algorithm and made some improvements.
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