Seite - 173 - in Document Image Processing
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J. Imaging 2017,3, 62
originaldocument images, theresulting imagesbeingcalledsemi-synthetic images in therestof the
paper. If there isnogroundtruthassociatedto thereal images,DocCreatorcancreate,withagiven
text, synthetic images that look like the real ones and their associated ground truth. Depending
on the needs and expertise of the user, DocCreator can be used in a fully automaticmode, or in
asemi-automaticmodewhere theusercan interactwith thesystemandtune itsparameters.Visual
feedback of the results is returned by the system. Degradations available inDocCreator can be
appliedonanytypeofdocument images. TheDocCreatorability tocreatesyntheticdocuments that
mimicrealones iseffective for typewrittenandhandwrittencharacters (as longas thecharactersare
apart fromoneanother). Images createdwithDocCreatorhavealreadybeenused inmanyDIAR
contexts: text/background/imagepixelclassification[36]; staff removal [13,37,38]; andhandwritten
character recognition [39]. In this article we present howDocCreator can be useful to enhance
a binarization algorithm and for OCR performance prediction. DocCreator could also be used,
forexample, forcamera-baseddocument imageanalysisandwordspotting.
Figure1.Accordingto theneedsof theDIARresearcher, it ispossible togeneratesyntheticdocument
images (andtheirgroundtruth) indifferentways. Firstpossibility: if a researcherhasrealdocument
imagesbutwithoutanyground truth,DocCreator cangenerate synthetic images that look like the
real ones, and of course, with the associated ground truth. Second possibility: a researcher has
aground-trutheddatabasebutit istoosmallornotheterogeneousenough.DocCreatorprovidesseveral
degradationalgorithmstoaugment thedataset. Bydegradingtext ink,papershapeorbackground
colours it is possible to create a representativedocument imagedatabasewheremanydefects are
present. Thiscompletedatabase isfinallyuseful forverypreciseperformanceevaluationor toprovide
multiplecases for retrainingprocesses (inalgorithmsembeddinga learningstep).
DocCreator features compared to existing software are highlighted in Table 1. First of all,
DocCreator is theonlyone that cancreate syntheticdocuments thatmimic realones. Besides, as it
includesseveraldegradationmodels, itprovidesanintegratedsolutiontocarryoutdataaugmentation.
DocCreator thusmakesquicklyavailableground-trutheddatabases. ItmakesDocCreatoraunique
software thatcanbeseenasacomplementary tool to thosementionedinTable1.
Thispaper isorganizedasfollows. InSection2,wepresent themethodsusedtoextractdocument
characteristicsandtogeneratesyntheticdocuments,while inSection3documentdegradationmodels
arediscussed. Section4highlights theadvantagesofDocCreatoronvariousDIAR tasks, both for
benchmarkingandforretrainingDIARtoolsusingdataaugmentation.
2.HowtoCreateaSyntheticDocument (withGroundTruth)ThatLooksLikeaRealOne?
TheleftpartofFigure1 illustrates thepipelineusedinorder togeneratesyntheticdocuments that
lookrealistic.Givenanoriginal image,weextract the threemainrequiredcomponents: (1) the font;
(2) the background; and (3) the layout of thedocument. The systemcan thenwrite any textwith
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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