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Document Image Processing
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J. Imaging 2018,4, 57 variantsarealsopresented inFigures10and11. Thedata inTable2 formsthebasis for thepoints in Figure10while thedata inTable3 formsthebasis for thepoints inFigure11. (a) (b) (c) (d) (e) (f) (g) (h) Figure 8. Pictorial comparisonbetween theperformances ofdifferentLBPbased featureswithRF Classifier.Here, (a)grayscale image, (b)groundtruth image, (c) resultusingLBP, (d) resultusingILBP, (e) resultusingRILBP, (f) resultusingULBP, (g) resultusingRIULBP,and(h) resultusingRULBP. 54
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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