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» Training on Severely Degraded Text-Line Images
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ICDAR
2003
IEEE
14 years 22 days ago
Training on Severely Degraded Text-Line Images
We show that document image decoding (DID) supervised training algorithms, as a result of recent refinements, achieve high accuracy with low manual effort even under conditions o...
Prateek Sarkar, Henry S. Baird, Xiaohu Zhang
ICDAR
2003
IEEE
14 years 22 days ago
Automatic Feature Selection with Applications to Script Identification of Degraded Documents
Current approaches to script identification rely on hand-selected features and often require processing a significant part of the document to achieve reliable identification. We p...
Vitaly Ablavsky, Mark R. Stevens
ICDAR
2007
IEEE
14 years 1 months ago
Exploiting Fisher Kernels in Decoding Severely Noisy Document Images
Decoding noisy document images is commonly needed in applications such as enterprise content management. Available OCR solutions are still not satisfactory especially on noisy ima...
J. Chen, Y. Wang
ICDAR
2009
IEEE
13 years 5 months ago
Document Image Binarisation Using Markov Field Model
This paper presents a new approach for the binarization of seriously degraded manuscript. We introduce a new technique based on a Markov Random Field (MRF) model of the document. ...
Thibault Lelore, Frédéric Bouchara
ISCAS
2008
IEEE
179views Hardware» more  ISCAS 2008»
14 years 1 months ago
Super resolution of video using key frames
— In many video compression systems, the frames are down-sampled before transmission. Also, in many scalable systems, the residual after down- and up-sampling is encoded and tran...
Fernanda Brandi, Ricardo L. de Queiroz, Debargha M...