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Lacunarity as a Texture Measure for Address Block Segmentation

机译:作为地址块分割的纹理度量

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摘要

In this paper, an approach based on lacunarity to locate address blocks in postal envelopes is proposed. After computing the lacunarity of a postal envelope image, a non-linear transformation is applied on it. A thresholding technique is then used to generate evidences. Finally, a region growing is applied to reconstruct semantic objects like stamps, postmarks, and address blocks. Very little a priori knowledge of the envelope images is required. By using the lacunarity for several ranges of neighbor window sizes r onto 200 postal envelope images, the proposed approach reached a success rate over than 97% on average.
机译:本文提出了一种基于Lavarity的方法来定位邮光信封中的地址块。在计算邮政包络图像的宽度之后,施加非线性变换。然后使用阈值化技术来产生证据。最后,应用区域生长以重建邮票,邮戳和地址块等语义对象。很少需要信封图像的先验知识。通过使用邻居窗口尺寸尺寸的几个范围的宽度,所提出的方法平均达到成功率超过97%。

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