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Document Image Processing
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J. Imaging 2017,3, 62 Figure5.Holedegradation. (Left)original images. (Right)degradedimages. 3.4. Bleed-Through WithDocCreator it ispossible toaddbleed-throughdefects. Thisalgorithmisdirectly inspired from[49] that initiallyproposesanalgorithmforerasingthebleed-throughfromadocument image. By justgivingan input recto image, an inputverso imageand theamountofwisheddegradation, a physicalmodel is applied. Thismodelmimics the verso ink that seeps through the recto side. Thismodel simulatesananisotropicdiffusionandeachpixelat time t+1 ismodifiedaccordingto the pixelsvaluesat time twiththe followingequation: It+1i,j = I t i,j+Ī»āˆ—(ctNi,j Ā· NIti,j+ctSi,j Ā· SIti,j+ctEi,j Ā· EIti,j+ctWi,j Ā· WIti,j) where I is the recto image, V is the verso image, lambda a constant value in [0;0.25] and N, S, E, W are themnemonic subscripts forNorth, South, East, West. NIti,j and ctNi,j are defined as: NIti,j =Vtiāˆ’1,jāˆ’ Iti,j and ctNi,j = 1 1+ (Vtiāˆ’1,jāˆ’I0i,j)2 σ2 . Theuser sets thenumberof iterationsand thus the quantityofgeneratedbleed-through. SeeFigure6 forableed-throughexample. Figure6.Bleed-throughdefect. (Left)original image. (Right)degradedimage. 177
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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