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Statistical Binarization Techniques for Document Image Analysis

机译:用于文档图像分析的统计二值化技术

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摘要

Binarization is an important process in image enhancement and analysis.Currently,numerous binarization techniques have been reported in the literature.These binarization methods produce binary images from color or gray-level images.This article highlights an extensive review on various binarization approaches which are also referred to as thresholding methods.These methods are grouped into seven categories according to the employed features and techniques: histogram shape-based,clusteringbased,entropy-based,object-attribute-based,spatial,local and hybrid methods.Most active binarization researchers exploit several initial information from the source image such as histogram shape,measurement space clustering,entropy,object attributes,spatial correlation and local gray level surface with a special attention to statistical information description features of image used in recent thresholding techniques.
机译:二值化是图像增强和分析的重要过程。目前,文献中报道了许多二值化技术。这些二值化方法从彩色或灰度级图像中生成二值图像。本文重点介绍了对各种二值化方法的广泛综述,这些方法也是这些方法根据所采用的特征和技术分为七类:基于直方图形状,基于聚类,基于熵,基于对象属性,空间,局部和混合的方法。来自源图像的一些初始信息,例如直方图形状,测量空间聚类,熵,对象属性,空间相关性和局部灰度表面,尤其要注意最近阈值化技术中使用的图像的统计信息描述特征。

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