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Document Image Processing
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J. Imaging 2017,3, 62 3.5.AdaptiveBlur Theblurdefect isaverycommondefectencounteredduringdigitizationcampaigns. Thedifficulty here is tocreatearealisticblurdefect thatmimics theveryslightblur thatappearswhenthescanner is incorrectlyset (a largeblur iseasilydetectedbyscanners). Todoso,weproposeamethodinspiredby theblurdetectionfrom[50]. First, theuserchoosesablur imagetomimicamongarealblurexample available inDocCreator. Then,usingadichotomicalgorithm,wecompute thesizeof thekernelof aGaussianblur that,onceappliedonthe input image,producesablursimilar to thechosenrealblur image. In thismethod, theFourierTransformof the image isfirst computed. Thenthemoduleof the FourierTransformisbinarizedaccordingto itsmean. Theresultingbinarized imageproducesadisc for imageswithonly text.As thehighfrequenciesdecreasewhentheblur increases, thedisc radius in thebinarized imagealsodecreaseswhen theblur increases. This radius isused tocharacterize the images. Thedichotomicalgorithmisusedtosearchthekernel size thatproducesaradiussimilar to theonefoundontheselectedexample image. SeeFigure7 foranexample. Figure 7. Adaptiveblurdefect. (Left) imagewith real blur. (Right) imagewith synthetic blur that mimics therealone 3.6. 3DPaperDeformation Thepaperonwhichabookisprintedmayhaveseveral typesofdeformation(alongcurvature, rotation, fold,hole, etc.).Weproposea3Ddeformationmodel thatgenerate realistic smallor large paperdeformations. Thefullprocessisdetailedin[51]. Themainideais: first,a3Dscannerisusedtoacquirea3Dmesh fromarealdocument. Thismeshpreservesall representativedistortions. Then, themesh isunfolded intoa2Dplan. Therefore,eachvertex in themeshhasacorresponding2Dpoint. Thecoordinatesof suchapoint are consideredas texture coordinates. Finally, themeshcanbe renderedwithany2D imagemappedasa texture. For therendering,weuse thePhongreflectionmodelas the illumination model. Changing lightproperties andpositionallows toaccentuateorminimizedistortioneffects. DocCreatorcurrentlyprovides17parameterizedmeshes, enablingone toproducenumerousdistorted images. Figure8showssuchadeformation. This3Dpaperdeformationmodelcanbeusedtosimulatemobiledocumentcapture. Theusercan addabackgroundplanewith texture,ontopofwhichthedocumentstands. Bychangingviewpoint andlightpositions, theusercangeneratemanyimages. These imagescanbeusedforcamera-based document imageanalysis. Figure9showsexamplesof twopointsofviewgeneratedwith thesame document image. 178
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Document Image Processing
Titel
Document Image Processing
Autoren
Ergina Kavallieratou
Laurence Likforman-Sulem
Herausgeber
MDPI
Ort
Basel
Datum
2018
Sprache
deutsch
Lizenz
CC BY-NC-ND 4.0
ISBN
978-3-03897-106-1
Abmessungen
17.0 x 24.4 cm
Seiten
216
Schlagwörter
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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Document Image Processing