文章基本信息

标题：Statistical Binarization Techniques for Document Image Analysis
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作者：Ismail, Saad M. ; Sheikh Abdullah, Siti Norul Huda ; Fauzi, Fariza 等
期刊名称：Journal of Computer Science
印刷版ISSN：1549-3636
出版年度：2018
卷号：14
期号：1
页码：23-36
DOI：10.3844/jcssp.2018.23.36
出版社：Science Publications
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, clustering-based, 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.
关键词：Document Image; Statistical Features; Thresholding; Binarization