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Document Image Analysis (DIA) Research:
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Page Segmentation:
Automatic extraction of the main document image components (text, titles,
images, captions, graphics, lines, special symbols) [], segmentation area
location using isothetic polygons [], newspaper page segmentation into
specific items (main titles, head-lines, over-titles, sub-titles,
references), article identification and reconstruction [],
combining complementary techniques for document image segmentation []. |
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Competitions:
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First International
Newspaper Segmentation Contest []
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ICDAR 2003 Page
Segmentation Competition []
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ICDAR2005 Page
Segmentation Competition []
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ICDAR2007 Page
Segmentation Competition []
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ICDAR2007 Handwriting
Segmentation Contest []
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ICDAR2009 Handwriting
Segmentation Contest [
]
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ICDAR 2009 Document Image
Binarization Contest (DIBCO 2009) [
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ICFHR 2010 Handwriting
Segmentation Contest []
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H-DIBCO 2010 – Handwritten
Document Image Binarization Competition []
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ICDAR 2011 Document Image
Binarization Contest (DIBCO 2011) []
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ICDAR 2011 Writer
Identification Contest []
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ICFHR 2012 Competition on
Handwritten Document Image Binarization (H-DIBCO 2012) []
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ICFHR2012 Competition on
Writer Identification - Challenge 1: Latin/Greek Documents []
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ICDAR 2013 Competition on
Writer Identification Document Analysis and Recognition []
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ICDAR 2013 document image
binarization contest (DIBCO 2013) []
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ICDAR 2013 Document Image
Skew Estimation Contest (DISEC 2013) []
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ICDAR 2013 Handwriting
Segmentation Contest []
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ICFHR2014 Competition on
Handwritten Document Image Binarization (H-DIBCO 2014) []
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ICFHR 2014 Competition on
Handwritten KeyWord Spotting (H-KWS 2014) []
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ICFHR2016 Handwritten
Keyword Spotting Competition (H-KWS 2016) []
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ICFHR2016 Handwritten
Document Image Binarization Contest (H-DIBCO 2016) []
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ICDAR2017 Competition on
Document Image Binarization (DIBCO 2017)
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cBAD: ICDAR2017
Competition on Baseline Detection
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ICDAR2017 Competition on
Historical Document Writer Identification (Historical-WI)
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Line and Table Detection:
Automatic table detection in document images, morphological operations in
order to connect line breaks and to enhance line segments, horizontal and
vertical line detection, image/text areas removal, detection of line
intersections, table reconstruction. []
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