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Segmentation of Postal Envelopes for Address Block Location: an approach based on feature selection in wavelet space

机译:地址块位置的邮政信封的分割:一种基于小波空间特征选择的方法

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This paper presents a segmentation algorithm based on feature selection in wavelet space. The aim is to automatically separate in postal envelopes the regions related to background, stamps, rubber stamps, and the address blocks. First, a typical image of a postal envelope is decomposed using Mallat algorithm and Haar basis. High frequency channel outputs are analyzed to locate salient points in order to separate the background. A statistical hypothesis test is taken to decide upon more consistent regions in order to clean out some noise left. The selected points are projected back to the original gray level image, where the evidence from the wavelet space is used to start a growing process to include the pixels more likely to belong to the regions of stamps, rubber stamps, and written area. Experiments are run using original postal envelopes from the Brazilian Post Office Agency, and here we report results on 440 images with many different layouts and backgrounds.
机译:本文介绍了基于小波空间特征选择的分割算法。目的是在邮政信封中自动分开与背景,邮票,橡皮图章和地址块相关的区域。首先,邮政信封的典型图像使用Mallat算法和HAAR分解。分析高频信道输出以定位突出点以分离背景。采取统计假设试验来决定更一致的区域,以清除一些噪音。所选点被投影回原始灰度级图像,其中来自小波空间的证据用于开始不断增长的过程,以包括更容易属于邮票,橡皮戳和书面区域的像素。使用来自巴西邮局机构的原始邮政信封进行实验,我们在这里向440个图像报告结果,其中包含许多不同的布局和背景。

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