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J. Imaging 2018,4, 57 in thepresentwork,wehaveamalgamatedtheconceptof ‘uniformpatterns’withRLBPtogenerate RULBP.TheformaldefinitionofRULBPisgivenbelow: RULBP(M,R)(xcen,ycen)= { ∑Mn=1 f(In− Icen− th), ifU(RILBP(M,R)(xcen,ycen))≥2, M+1, otherwise. (10) ThevalueofU(RLBP(M,R)(xcen,ycen)) is computedusingEquation(8). 2.5.2. SelectingtheValueof th FromEquation(9), it canbe inferredthat the threshold(th) inRLBPplaysan important roleand whosevaluemightbeapplicationspecific tosomeextent. Thus, in thiswork,wehaveattemptedto rationalize it in thecontextof text/non-text separation inhandwrittendocuments. Mosthandwrittendocumentsgenerallypossessa large intensityvariationat thestroke leveldue tothevariednatureofwritinginstrumentsandnon-uniformityintheamountofpressureappliedwhile writing. Thisnon-homogeneityoverasinglestrokecanonlybe identified ifwemagnify the image (see thedarkandbrightpatcheswithin thestroke inFigure5. Forexample,LBPfor the3×3segment, markedinred, inFigure5 is ‘00010001’.However, thevisualperceptionofahumanbeingconsiders thisasahomogeneousregionwithall zeros ‘00000000’. Thispropertyofhandwrittendocumentsmay generateerroneousLBPfeaturevalues,which, in turn, fail todistinguish the textcomponents fromthe non-textones. Inorder tosolvesuchproblems,a threshold ‘th’hasbeen introducedinLBPtogenerate RLBP.This thresholdensures that twograyvalues thatarenotperceptiblydifferentarenot labeled differently. Theproblemwithselectingavalueof th is that, if thevalue isextremely large, thenthe entire regionwillbehave likeahomogeneousregionwithnointensityvariation. This isbecause the binarypattern ,according toEquation (10),will be all zeros for everypixel. Therefore,weneed to provideanupper limit, thmax , on thevalueof th. Figure5.Magnifiedimageofastrokeshowsthevariation ingrayvalues.A3×3matrixshowsthe intensityvaluesof thegray imagesegmentmarkedinred. Toaddress this issue,wehavesetanupper limit, thmax , onthevalueof th. Generally, inareal-life handwrittendocument image, the intensityof thebackgroundpixels residewithinacloseproximity of themaximumintensity255.Here,weassumethat the intensityof thebackgroundpixelswillbe ina rangeof [245,255].Now,foreachimage,wefindthehighestgray-scale intensity(Igraymax) less than245. Weclaimthat thepixelPhavingthis intensityvaluehas tobeapartof somewritingstroke. thmaxhas tobesuchthat, ifweconsider Icenhasavalue Igraymax andaneighboringpixelhasavalue245, f(x) as given inEquation (2) for x= In− Icen− thgives avalue 1. Therefore, thmax = 245− Igraymax. Thevalueof thcanbeanythingbetween thmax and0.Wehaveperformedaweightedaverageof the thresholdvalues in therange,with theweights increasingforhighervaluesof thandfoundthe ideal 50
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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