Modified Sauvola binarization for degraded document images

dc.contributor.authorKaur, A
dc.contributor.authorRani, U
dc.contributor.authorJosan, G.S.
dc.date.accessioned2020-07-16T07:41:55Z
dc.date.accessioned2024-08-14T05:05:53Z
dc.date.available2020-07-16T07:41:55Z
dc.date.available2024-08-14T05:05:53Z
dc.date.issued2020
dc.description.abstractThe binarization of historical documents is a difficult job due to the presence of many degradations. Many existing local binarization techniques use certain manually adjusted parameters. The output of these techniques is much dependent on the value of these parameters. One of such parameters is window size which is kept fixed for the whole text image. The fixed window size will not be able to perform well for images having variable stroke widths and text sizes. The proposed binarization technique (Modified Sauvola) is the modification of state of art Sauvola's binarization technique. It automatically computes window size dynamically across the image pixel to pixel using the stroke width transform (SWT). This led to reduction in number of manually adjusted parameters. The results are compared with the nine existing techniques using the quantitative measures: FM, PSNR, NRM, MPM, and DRD. The results show that the proposed method outperforms existing methods for images having variable stroke widths and text sizes. - 2020 Elsevier Ltden_US
dc.identifier.doi10.1016/j.engappai.2020.103672
dc.identifier.issn9521976
dc.identifier.urihttps://kr.cup.edu.in/handle/32116/2654
dc.identifier.urlhttps://www.sciencedirect.com/science/article/abs/pii/S0952197620301159
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.subjectBinarization techniquesen_US
dc.subjectDegraded document imagesen_US
dc.subjectHistorical documentsen_US
dc.subjectStroke width transformen_US
dc.titleModified Sauvola binarization for degraded document imagesen_US
dc.title.journalEngineering Applications of Artificial Intelligenceen_US
dc.typeArticleen_US
dc.type.accesstypeClosed Accessen_US

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