@inproceedings{2a4a5a8c7d9e43c699f5a1c9c61e239a,
title = "Nested state indexing in pairwise Markov networks for fast handwritten document image rule-line removal",
abstract = "The Markov random field (MRF) has been applied to modeling the connectivity constraints of the text in document images for tasks like binarization and rule-line removal. One challenge of applying the MRF is its high computational cost. This paper presents a method using two nested set of states trained to reduce the computational cost of patch-based MRF. The two sets of states are trained at different levels in coarse-to-fine order. We show effective reduction of run time but very little loss of quality using rule-line removal experiments.",
author = "Huaigu Cao and Rohit Prasad and Premkumar Natarajan and Venu Govindaraju",
year = "2009",
doi = "10.1109/ICIP.2009.5413806",
language = "English",
isbn = "9781424456543",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "2009--2012",
booktitle = "2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings",
address = "United States",
note = "2009 IEEE International Conference on Image Processing, ICIP 2009 ; Conference date: 07-11-2009 Through 10-11-2009",
}