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An integral criterion for detecting boundary edges and textured regions

机译:检测边界边缘和纹理区域的整体标准

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Edge maps which are computed from textured scenes using existing methods based on local image analysis are not very meaningful. This is because edges at object boundaries are not differentiated from edges in texture. We introduce a real-time algorithm that overcomes this difficulty by computing the Dirichlet integral in a small image patch at different scales. These measurements are combined and interpreted in a probabilistic framework avoiding the need for a threshold. As a result the output of this algorithm can be utilised by a higher level process. Texture does not fit our model of a boundary edge thus its presence is detected by the probabilistic model as an outlier. Convincing results are shown on synthetic as well as images of the natural world. This algorithm is intended to be a fast preprocessing step for localising boundary edges and textured image regions.
机译:使用基于局部图像分析的现有方法从带纹理的场景中计算出的边缘图不是很有意义。这是因为对象边界处的边缘与纹理中的边缘没有区别。我们介绍了一种实时算法,该算法可以通过在不同比例的小图像补丁中计算Dirichlet积分来克服此难题。这些测量在概率框架中进行合并和解释,从而无需阈值。结果,该算法的输出可以被更高级别的过程利用。纹理不适合我们的边界边缘模型,因此概率模型将其检测为异常值。令人信服的结果显示在合成图像以及自然世界的图像上。该算法旨在成为定位边界边缘和纹理图像区域的快速预处理步骤。

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