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A hybrid algorithm for segmentation of range images

机译:距离图像分割的混合算法

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摘要

The authors present a technique for the segmentation of range images. It tends to be a hybrid approach that combines edge detection and region growing techniques for accomplishing the task of segmentation. The surface coherency property of range data is an important attribute of the technique. The cross-breeding approach produces a segmentation map and an edge map. The incorporation of the region growing process eliminates internal micro edges and produces a segmentation map. These two maps would undoubtedly be of great value for the higher-level recognition process. Experimental results show that the edges detected and the regions partitioned tend to have a good localization property.
机译:作者提出了一种用于距离图像分割的技术。它趋向于是一种混合方法,将边缘检测和区域增长技术相结合来完成分割任务。距离数据的表面相干性是该技术的重要属性。杂交方法产生了一个分割图和一个边缘图。区域生长过程的合并消除了内部微边缘,并产生了分割图。毫无疑问,这两张地图对于更高级别的识别过程将具有巨大的价值。实验结果表明,检测到的边缘和区域划分趋于具有良好的定位性能。

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