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J. Imaging 2018,4, 32
Figure6.Exampleof text images fromAcTiV-Rdepictingtypical characteristicsofvideotext images.
3.2.AnnotationGuidelines
Weutilized theAcTiV-GT tool [47] to annotate our collectionofdata. Figure 7 illustrates the
user interfaceof this tool. In theannotationprocess,wecollect the following information for each
text rectangle.
• position: x,y,widthandheight.
• content: text strings, textcolor,backgroundcolor,backgroundtype(transparent,opaque).
• Interval: apparition intervalof the textline (Frame_S(Start),Frame_E(End)).
Note thata text rectanglecan includemultiple lines if theyshare thesamefont, colorandsize,
andif theyarenot far fromeachother.
Caseof static text annotation:
Determine (1) spatial coor. of
the current text , (2) its color,
(3) its bg type and color, next
(4) its apparition interval
List of video frames
and visualization of
the transcriptions'
information
Visualization of the layout coor.
(x, y, w, h) and of the fd/bg color
Figure7.AcTiV-GTopen-source tooldisplayinga labeledframe.
This set of information is saved in ametafile calledglobalXMLfile (an extract is illustrated
inFigure8). Thisfile canbeused for trackingandend-to-end tasks. InAcTiV2.0, twoadditional
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Buch Document Image Processing"
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
- Kategorie
- Informatik