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A New Wavelet-Based Document Image Segmentation Scheme

机译:基于小波的文档图像分割方案

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摘要

The document image segmentation is very useful for printing, faxing and data processing. An algorithm is developed for segmenting and classifying document image. Feature used for classification is based on the histogram distribution pattern of different image classes. The important attribute of the algorithm is using wavelet correlation image to enhance raw image's pattern, so the classification accuracy is improved. In this paper document image is divided into four types: background, photo, text and graph. Firstly, the document image background has been distingusished easily by former normally method; secondly, three image types will be distinguished by their typical histograms, in order to make histograms feature clearer, each resolution' s HH wavelet subimage is used to add to the raw image at their resolution. At last, the photo, text and praph have been devided according to how the feature fit to the Laplacian distrbution by -X2 and L. Simulations show that classification accuracy is significantly improved. The comparison with related shows that our algorithm provides both lower classification error rates and better visual results.
机译:文档图像分割对于打印,传真和数据处理非常有用。开发了一种用于分割和分类文档图像的算法。用于分类的功能基于不同图像类的直方图分布模式。算法的重要属性是使用小波相关图像来增强原始图像的模式,因此提高了分类精度。在本文中,文档图像分为四种类型:背景,照片,文本和图形。首先,文件图像背景已经通过前一般方法轻松分离;其次,将通过典型的直方图区分三种图像类型,以便使直方图具有更清晰的功能更清晰,每个分辨率的HH小波单元用于以其分辨率添加到原始图像。最后,照片,文本和普遍存在的特征如何适应Laplacian Distrumution的-X2和L.模拟表明,分类准确性显着提高。与相关的比较表明,我们的算法提供较低的分类误差率和更好的视觉结果。

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