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J. Imaging 2018,4, 80 homogenousslant. Itdoesnot requirepagesegmentation into text linesorwords. Thismakes the proposedtechniqueappropriate forhistoricaldocuments, especially formalones, since theyensure auniformslantover theentirepage.Moreover, thesegmentation into text lineswouldcreatemore noise. Usually, formal historical documents arewrittenbywell-educatedpeoplewith a standard writing style andfixed slant. On the other hand, the proposedmethodology is inappropriate for document imagescontainingunconstrainedwritingandseveral slantangles.Methodologies, such as theonedescribedin[6], aremoreappropriate insuchcases. Thus,experimentsareperformedon severaldatabases: • theTrigraphSlantdatabase [18] (theonlyavailabledatabase forslantestimation), • two databases of historical documents (George Washington [19] and Barcelona historical, handwrittenmarriagesdatabaseBH2M[20]) • asyntheticprinteddatabasewhereslantsare fullydetermined. Thecontributionof thecurrentworkconsistsof: 1. To thebestofourknowledge, this is thefirst time thata slant removal technique isproposed, able tobeappliedto theentirepage,withoutrequiringtext lineorwordsegmentation. 2. It does not generate extra noise, due to line and/orword segmentation thatwould remain in thepage after slant removal,which is accomplishedby shifting the entirepageuniformly andensuring texthomogeneity. Mostof theexisted techniquesapply to idealdatabases, like IAM-DB(Figure1) that is appropriatelymade for lineandwordsegmentation. In thecaseof historical documents (Figure 2), thefinal resultwouldbe full of dots and strokes because of thesegmentation. 3. Instructionsaregivenover thebestapplicationtodocumentpage,afterdetailedresults. In Section2.1, a shortdescriptionof the elaborated slantdetectionalgorithm[9] is presented. Theproposedtechnique isdescribed indetail inSection2.2,where theparameters thatareexamined indetail areanalyzed. Theexperimental results arepresentedandanalyzed inSection3while the conclusionsarediscussed inSection4. Figure2.Adocument fromtheBarcelonahistorical,handwrittenmarriagesdatabase (BH2M)[20]. 31
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Document Image Processing
Title
Document Image Processing
Authors
Ergina Kavallieratou
Laurence Likforman-Sulem
Editor
MDPI
Location
Basel
Date
2018
Language
German
License
CC BY-NC-ND 4.0
ISBN
978-3-03897-106-1
Size
17.0 x 24.4 cm
Pages
216
Keywords
document image processing, preprocessing, binarizationl, text-line segmentation, handwriting recognition, indic/arabic/asian script, OCR, Video OCR, word spotting, retrieval, document datasets, performance evaluation, document annotation tools
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Informatik
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Document Image Processing