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J. Imaging 2018,4, 80 Themeasureusedtoevaluate the technique is theroot-mean-squareerror (RMSE) RMSE= √√√√√ N∑d=1 ( Slantdgr−Slantdes )2 N (6) whereSlantgr isthegroundtruthslantofdocumentdandSlantes theslantestimatedusingthetechnique. Thismeasuregives a comparative result that is independent of the right or left slantdirection. N refers to the amount of documents. Next, a short descriptionof thedatabases is given,while the setupontheparameters follows.As initialparametervalues, theparametersusedin[17]areusedin ourexperiments,andassoonas thebestparametervalue isestimated, it isusedfurtheron. Finally, experimental results for the fourdatabasesarepresented(seeSection3.9). 3.1. TrigraphSlantDB TheTrigraphSlant [18]database contains imagesofhandwritingproducedundernormaland forcedslantconditions. It includes190handwrittendocument images,writtenby47people. Foreach image, the slant has been estimated by two researchers (Axel and Rolland) from the average slant computed from10measurements on eachdocument image. In Figure 6, an example of the TrigraphSlantdatabaseafter theapplicationof theproposedtechnique isshown. Figure6.Applicationof the techniqueonasample fromtheTrigraphSlantdatabase (left); correctedby +28degrees (right). 3.2.GeorgeWashingtonDB This archive contains a set of 20 page images from theGeorgeWashington collection [19] at theLibraryofCongress in theUnitedStates. Aprocess similar to that used for theTrigraphSlant databasewas followed. Ten slantsweremeasuredby twohumansoneachpageand themeanof thesemeasurementswasconsideredtobethepageslant. Figure7showsanexampleof theGeorge WashingtonDBafter theapplicationof the technique. 36
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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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Austria-Forum
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Document Image Processing