Binarization of uneven-lighting image by maximizing boundary connectivity

Tung, Cheng-Huang; Wu, Zong-Lin

doi:10.1080/09720510.2016.1241469

Cited by 8 publications

(2 citation statements)

References 11 publications

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“…high noise, poor contrast, low illuminations, spots and patches, etc) -the images' characteristics are not leveraged. On the other hand, in local thresholding methods, the threshold values are determined locally either pixel by pixel (Kasmin et al, 2017;Niblack, 1985;Sehad et al, 2013) or region by region (Neves and Mello, 2011;Pai et al, 2010;Tung and Wu, 2017). Then, a specified region can have a threshold value that is changed from region to region according to the threshold candidate selection for a given area.…”

Section: Discussionmentioning

confidence: 99%

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Statistical Binarization Techniques for Document Image Analysis

Ismail

Abdullah

Fauzi

2018

Journal of Computer Science

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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.

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Section: Discussionmentioning

confidence: 99%

“…Ntirogiannis method = ∑ ∑ (Tung and Wu, 2017) Hybrid/Objective where TH(x, y) is the threshold value of (x, y) in the threshold attribute-based surface, N t . TH and N t. DIS the threshold and the distance of for (x, y) respectively…”

Section: Hybrid Methodsmentioning

confidence: 99%