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Document Image Processing
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J. Imaging 2018,4, 57 Table3.ClassificationresultsusingvariousthresholdsforRULBP.Theclassificationaccuracygradually increasesandattainsamaximumata thof105units. FeatureDimension Threshold(th) Precision Recall F-Measure Accuracyin% 5 0.915 0.915 0.914 91.45 25 0.915 0.915 0.915 91.52 45 0.916 0.916 0.915 91.61 59 65 0.917 0.917 0.917 91.72 85 0.919 0.918 0.918 91.84 105 0.920 0.920 0.919 91.96 115 0.919 0.918 0.918 91.84 Figure10.Graphical comparisonof theperformancesofdifferentLBPvariants inclassifyingthe texts andnon-textspresent inhandwrittendocument images. Figure11.Graphical comparisonof theperformancesofRULBPwithdifferent threshold inclassifying the textsandnon-textspresent inhandwrittendocument images. 56
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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
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Informatik
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Document Image Processing