1. Quality Assessment and Restoration of Typewritten Document Images, Michael Cannon, Judith Hochberg, and Patrick Kelly, Los Alamos National Laboratory, LA-UR 99-1233. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.31.2293.pdf (24 pages long, but really only about half that length because of the spacing).

2.  Souza, A.; Cheriet, M.; Naoi, S.; Suen, C.Y. Automatice Filter Selection Using Image Quality Assessment.  In Proceedings of Document Analysis and Recognition (ICDAR), vol. 1, pp. 508-512, Aug. 2003. http://www.cse.salford.ac.uk/prima/ICDAR2003/Papers/0093_626_souza_a.pdf (5 pages)

3.  M. Agrawal and D. Doerman.  Clutter Noise Removal in Binary Document Images.  ICDAR09, pp. 556-560, 2009.  http://lampsrv02.umiacs.umd.edu/pubs/Papers/mudit-clutter09/mudit-clutter09.pdf (5 pages)

4.  Machine Printed Text and Handwriting Identification in Noisy Document Images, Yefeng Zheng, Huiping Li, and David Doerman, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 3, March 2004, pp. 337-353.  http://www.cse.lehigh.edu/~lopresti/tmp/PAMI04.pdf (17 pages)

5.  Optical Character Recognition Errors and Their Effects on Natural Language Processing, Daniel Lopresti, International Journal on Document Analysis and Recognition, Volume 12, Number 3/September 2009, pp. 141-151.  http://www.cse.lehigh.edu/~lopresti/tmp/AND08journal.pdf (11 pages)

6.  Spatial Sampling of Printed Patterns, Prateek Sarkar, George Nagy, Jiangying Zhou, and Daniel Lopresti, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 3, March 1998, pp. 344-351.  http://www.cse.lehigh.edu/~lopresti/tmp/PAMI98.pdf (8 pages)

7.  Xu, C. and Prince, J.  Snakes, Shapes, and Gradient Vector Flow.  IEEE Trans. on Image Processing, 7(3):359-369, 1998.  http://iacl.ece.jhu.edu/pubs/p084j.pdf (11 pages)

8.  Pizer, S.M., Fletcher, P.T., et al.  Deformable M-reps for 3D medical Image Segmentation, International Journal of Computer Vision, Special Issue on UNC-MIDAG Research, 55(2-3):85-106, 2003.  http://midag.cs.unc.edu/pubs/papers/IJCV03-Pizer-mreps.pdf (22 pages)

9.  Sundar, H., Silver, D., Gagvani, N. and Dickinson, S. Skeleton Based Shape Matching and Retrieval.  Proc. Of International Conf. on Shape Modeling, pages 130-139, 2003.  http://www.cs.toronto.edu/~sven/Papers/smi2003.pdf (10 pages)

10.  Bai, X., Wang, X., Liu, W., Latecki, L.J. and Tu, Z.  Active Skeleton for Non-rigid Object Detection.  Proc. Of International Conf. on Computer Vision, 2009.  http://xiang.bai.googlepages.com/ActiveSkeleton.pdf (8 pages)

11.  Wells, W.M., Viola, P., Atsumi, H., Nakajima. S. and Kikinis, R.  Multi-modal volume registration by maximization of mutual information.  Medical Image Analysis, 1(1):35-51, 1996.  http://people.csail.mit.edu/sw/papers/mia.pdf (20 pages)

12.  Brillinger, D.R. & Guha, A. Mutal Information in the Frequency Domain.  Journal of Statistical Planning and Inference, 137(3):1076-1084, 2007.  http://www.stat.berkeley.edu/~brill/Papers/purifinal.pdf (9 pages)