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J. Imaging 2018,4, 39 Figure7.Samplewordimageswritten in12different Indianscripts. OurdevelopeddatabasehasbeennamedasCMATERdb8.4.1,whereCMATERstands for ‘Centre for Microprocessor Applications for Training Education and Research,’ a research laboratory at Computer Science andEngineeringDepartment of JadavpurUniversity, India,where the current database is prepared. Here, db symbolizes database, the numeric value 8 represents handwritten multi-script Indic imagedatabaseandthevalue4 indicatesword-level. In thepresentwork, thefirst versionofCMATERdb8.4hasbeenreleasedasCMATERdb8.4.1. Thedatabase ismadefreelyavailable athttps://code.google.com/p/cmaterdb/. 4.2. PerformanceAnalysis Theclassifiercombinationapproaches,describedabove,areappliedonadatasetof7200words dividedinto12classeswithequalnumberof instances ineachof them. 12classes refer to the12 Indic scripts thathavebeenstudiedbeforeandforwhich theMLPclassifier results canbeobtainedwith highaccuracy. TheclassesnumberedfromA toLareDevanagari,Bangla,Oriya,Gujarati,Gurumukhi, Tamil,Telugu,Kannada,Malayalam,Manipuri,UrduandRoman in thatparticularorder. 159
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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