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J. Imaging 2017,3, 62
images;and(3) font,backgroundandlayoutarefinallyusedwiththetranscribedtexts toautomatically
generate syntheticversionsof theoriginal ones. Thewholedatabase is composedof 93document
imagescontaining18.240wordsand115.622characters.
(a) (DB1)Contemporaryfrenchtypewrittendocument.
(b) (DB2)Oldfrenchtypewrittendocument.
(c) (DB3)OldfrenchManuscriptdocument.
Figure11. Imagesextractedfromthedatabaseusedfor testingourpredictionalgorithm. (Left)original
images. (Right) syntheticgenerated images.
Toevaluate theOCRtext recognitionrate,weuse theLevenshteindistance (ametricmeasuring
the difference between two strings) between the whole original transcribed text and the whole
recognized text. Wecompute themeanof theLevenshteindistances for theNdocuments of each
database. Using this Levenshtein distance, the difference between theOCR text recognition rate
computedonreal imagesandtheonecomputedon“Loremipsum”version(Table2Column1and
Column2) is, on average, only overestimated by 0.04. Thedifference between the realOCR rate
and theone computedon the synthetic versions (Table 2Column1andColumn3) is, onaverage,
onlyoverestimatedby0.03.Mostof thesuccessofdifferentexistingOCRpredictionmethods ([63–66])
arerelatedto thequalityandquantityof theneededgroundtruth.Ourpredictionmethodpresented
hereprovidescomparableresultswith theones formthestateof theart.
Table2.ComparisonbetweenOCRrecognitionratesobtainedonthreedifferentbooksoriginal images
and their syntheticversions. Column1: OCRrecognition rateonoriginal images,Column2: OCR
recognitionrateonsynthetic imagesgeneratedwithboththetextandthefont fromtheoriginal images,
Column3:OCRrecognitionrateonsynthetic imagesgeneratedwith loremipsumrandomtextandthe
font fromtheoriginal images.
Original Image FontFrom SameText LoremText
DB1 0.95 DB1 0.94 0.88
DB2 0.80 DB2 0.85 0.84
DB3 0.24 DB3 0.21 0.23
5.Conclusions
DocCreator gives toDIAR researchers a simple and rapidway to extend existing document
imagedatabasesor tocreatenewonesavoidingthe tedious taskofmanualgroundtruthgeneration.
DocCreator embeds many fonts, backgrounds, meshes and realistic degradation models which,
whencombined, result inan interestingcombinationofground-trutheddatabases. Theexperiments
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book Document Image Processing"
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
- Category
- Informatik