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J. Imaging 2018,4, 39
majorandminoraxesequaltothewidthandtheheightoftheboundingboxandthecentreofanellipse
isalso thecentreof thecorrespondingboundingbox. Thisellipsedivides thewordimage intoeight
regionsRi, I=1,2 . . . , 8. Theboundingboxalongwith the inscribedellipse forahandwrittenBangla
word imageare shown inFigure2b. Taking thevaluesofPr fromtheseeight regions, as shown in
Figure2a,eight features (F1âF8) foreachhandwrittenwordimageareestimated.Now,another typeof
feature,PcalongN(N=8for thepresentwork) linesparallel tomajor/minoraxisof therepresentative
ellipsearecomputed. Themeanandstandarddeviationof thevaluesofPcalongmajor/minoraxisare
takenas fouradditional features (F9âF12).
Figure 2. Illustration of ïŹtting (a) an imaginary ellipse inside theminimumboundary boxwhich
dividesaBanglahandwrittenwordimage in8regionsasshownin(b).
2.1.2. Sectional InscribedEllipse
Eachof thewordimagessurroundedbytheminimumboundingbox isagaindividedinto four
equalrectanglesandarepresentativeellipseisïŹt intoeachoftheserectanglesusingthesameprocedure
asdescribed in theprevioussubsection. Asa result, everyellipseproduceseight regions inside its
rectangular area namely,Rij where 1†i †4 and1†j†8whichmakes 8à 4= 32 regions in
total. Atotalof32 featurevalues (F13âF44)using thePrvalues is computedfromthe32ellipses in
similar fashion.
2.1.3.ConcentricEllipses
These featurevaluesarecomputedbytakingtheentire topologyof thewordimage.Aprimary
ellipse ismadecircumscribingthewordimagewithcentre takentobethemidpointof itsminimum
boundingbox. Thevaluesof themajor andminor axesof the ellipse are taken into consideration.
AfterïŹttingtheprimaryellipse, threeconcentricellipsesaredrawninside theprimaryellipsehaving
thesamecentrepointas theprimaryellipseandmajorandminoraxesequal to1/4th,2/4thand3/4th
ofmajor andminoraxesof theprimaryellipse respectively. These four ellipsesdivideeachof the
wordimages into fourregions-Re1,Re2,Re3 andRe4. Thepartitioningof the fourregionsonasample
handwrittenDevanagariwordimage is showninFigure3. Fromthefourregions, four featuresvalues
(F45âF48)consideringthePrâsandfourfeaturevalues(F49âF52)consideringthePcâsof theregionsRe1,
Re2,Re3 andRe4areestimated. Theremainingsixfeatures(i.e.,F53âF58)aretakenasthecorresponding
differencesof thePrâsandPcâsbetweentheregionsRe1 andRe2,Re2 andRe3,Re3 andRe4 respectively.
Theelliptical features (F1âF58)aresuitablynormalizedbytheheightandwidthof thecorresponding
wordimage.
Figure3.Figureshowingtheellipticalpartitionof fourregionsonasamplehandwrittenDevanagari
wordimage.
153
zurĂŒck zum
Buch Document Image Processing"
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
- Kategorie
- Informatik