Quite a bit of work has been done on uScript in the last 10 years. Here is where all of the research is kept!
Previous Student Theses
Current research to further the project
Document Image Analysis toolbox–A paper describing algorithms for analyzing a document and performance metrics for each of the tasks presented.
J. Liang, R. Rogers, R.M. Haralick, and I.T. Phillips.
Reactions: useful analysis of a wide variety of methods. Includes simulation of noisy documents. Conclusions are drawn in paper: clustering-based methods and locally adaptive methods are best for document binarization. Kittler method found to be most effective
Reactions: Conceptually interesting technique, because not only does it do BOTH segmentation and binarization from the grayscale image, but it does so using local adaptive and clustering methods for binarization. Difficult to follow the exact details of the scheme, as the English in the document needs some work.
From ICDAR 2001
Solution to binarization based on noise reduction in the source image. Reactions: Doesn’t sound like it’s what we need–the noise they focus on is not similar to what seems to be our primary problem, which is some words being lightere than others, or obscured in stained areas of the document.