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首页> 外文会议>Biennial Australian Pattern Recognition Society Conference(DICTA2003) v.2; 2003; Sydney; AU >Two-Level Image Segmentation Based on Region and Edge Integration
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Two-Level Image Segmentation Based on Region and Edge Integration

机译：基于区域和边缘融合的两级图像分割

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摘要

This paper introduces a two-level approach for image segmentation based on region and edge integration. Edges are first detected in the original image using a combination of operators for intensity gradient and texture discontinuities. To preserve the spatial coherence of the edges and their surrounding image regions, the detected edges are vectorized into connected line segments which serve as the basis for a constrained Delaunay triangulation. Segmentation is first performed on the triangulation using graph cuts. Our method favors segmentations that pass through more vectorized line segments. Finally, the obtained segmentation on the triangulation is projected onto the original image and region boundaries are refined to achieve pixel accuracy. Experimental results show that the two-level approach can achieve accurate edge localization, better spatial coherence and improved efficiency.
机译：本文介绍了一种基于区域和边缘融合的两级图像分割方法。首先使用强度梯度和纹理不连续性运算符的组合在原始图像中检测边缘。为了保持边缘及其周围图像区域的空间连贯性，将检测到的边缘矢量化为连接的线段，这些线段用作约束Delaunay三角剖分的基础。首先使用图割对三角剖分进行分割。我们的方法支持通过更多矢量化线段的分段。最后，将在三角剖分中获得的分割投影到原始图像上，并细化区域边界以实现像素精度。实验结果表明，该两级方法可以实现精确的边缘定位，更好的空间相干性和更高的效率。

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