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Parallel distributed algorithm for texture boundary localization

机译:并行分布式纹理边界定位算法

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Abstract: In most instances the boundaries between textured regions are defined by the gray level contrasts which result from the local interaction between the texture elements in each region. In such cases, the boundaries can be accurately characterized by gray level edge segments. Using these edge segments to localize the texture boundary directly addresses the major problem associated with texture segmentation, namely the localization verses classification accuracy conflict. The accuracy of segmentation methods which rely only on spatially distributed properties to characterize the texture, is limited to the spacial extent of the property used. In contrast, gray level edges are significantly more localized. However, before they can be of any use, the gray level edge segments defining the texture boundary must be isolated from the edges defining the texture elements. In this paper, we define a set of properties to do this. We also incorporate these properties into a parallel distributed algorithm which is used to segment a set of sample texture images. !12
机译:摘要:在大多数情况下,纹理区域之间的边界是由灰度对比定义的,灰度对比是由每个区域中纹理元素之间的局部交互作用导致的。在这种情况下,边界可以通过灰度级边缘段准确表征。使用这些边缘片段来定位纹理边界直接解决了与纹理分割相关的主要问题,即定位与分类精度冲突。仅依赖于空间分布的属性来表征纹理的分割方法的准确性受限于所使用属性的空间范围。相反,灰度级边缘的位置明显更大。但是,在将其用于任何用途之前,必须将定义纹理边界的灰度级边缘段与定义纹理元素的边缘隔离开。在本文中,我们定义了一组属性来执行此操作。我们还将这些属性合并到并行分布式算法中,该算法用于分割一组样本纹理图像。 !12

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