基于纹理法和模糊聚类的行政文件分割

Wala Zaaboub, Lotfi Tlig, M. Sayadi
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引用次数: 1

摘要

文档图像分割是文档布局分析系统中不可缺少的一项任务。提出了一种基于模糊分类的行政文件图像精确分割方法。针对这类文档图像的基于纹理的分析工作很少。针对具体任务的研究工作是有限的。此外,基于纹理的分割方法是需要的,因为它们不强烈依赖于文档周围的先验知识。此外,这些方法对于退化文档的鲁棒性也得到了证明。出于这些目的,纹理在我们的图像类型的分析中进行了探索,使用模糊分类。Fisher分数决定了我们分割的最具判别性的纹理特征:均值和方差。我们的方法在检测文档区域(文本、图像和背景)方面取得了令人鼓舞和有希望的结果。提出了定性和定量实验来确定我们的方法性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Administrative document segmentation based on texture approach and fuzzy clustering
The document image segmentation is an indispensable task in the document layout analysis system. This paper presents an accurate segmentation approach based on fuzzy classification for the administrative document image. The texture-based analysis works for this kind of document image are rare. And the research works on specific tasks are limited. Moreover, the texture-based segmentation methods are desired because they do not rely strongly on a priori knowledge surrounding the document. In addition, the robustness of these methods for degraded documents has been proven. For these purposes, the texture is explored in the analysis for our image type, using a fuzzy classification. The Fisher score determinate the most discriminative texture features for our segmentation: mean and variance. Our approach achieves encouraging and promising results for the detection of document zones: text, image and background. Qualitative and quantitative experiments are presented to determinate our approach performance.
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