Degraded Document Recognition is a subclass of Optical Character Recognition that specifically addresses the challenge of accurately extracting and interpreting textual content from documents impaired by noise, distortions, low resolution, or other forms of degradation.
197
Publications
7.5K
Citations
473
Authors
189
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Publications per year
2017–2026
42
Publications
197
An adaptive logical method for binarization of degraded document images
Yibing Yang, Hong Yan · Pattern Recognition · 2000 · 190 citations
1–5 of 197
Authors
473
- MC
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- PN
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- DD
6
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1–5 of 473
Institutions
189
University at Buffalo, State University of New York
Buffalo, United States
8 h-index
16 publications
375 citations
Palo Alto Research Center
Palo Alto, United States
7 h-index
10 publications
297 citations
École de Technologie Supérieure
Montreal, Canada
7 h-index
15 publications
821 citations
University of Maryland, College Park
College Park, United States
6 h-index
13 publications
1.1K citations
AT&T (United States)
Bedminster, United States
5 h-index
11 publications
803 citations
National University of Singapore
Singapore, Singapore
5 h-index
11 publications
421 citations
University of Kaiserslautern
Kaiserslautern, Germany
5 h-index
8 publications
210 citations
Jadavpur University
Kolkata, India
5 h-index
13 publications
412 citations
1–8 of 189
Venues
- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
11 publications · 205 citations
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- Pattern Recognition
10 publications · 949 citations
10
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- International Journal on Document Analysis and Recognition (IJDAR)
9 publications · 395 citations
9
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- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 8 publications · 1.5K citations
8
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- Optik
2 publications · 91 citations
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1–5