Citation
Plamondon, Réjean, and Sargur N. Srihari. "Online and off-line handwriting recognition: a comprehensive survey." Pattern Analysis and Machine Intelligence, IEEE Transactions on 22.1 (2000): 63-84.
Summary
This is a survey paper providing an breath view of different online and offline handwriting recognition techniques, discussing the state of the art and many other techniques specific to certain domains. For offline handwriting recognition the paper discusses a variety of preprocessing steps, which include thresholding, noise removal, line segmentation (which is an important problem already thoroughly discussed in previous readings), word and character segmentation. Then comes the character recognition step, which can be divided into two main areas, mainly OCR (Optical Character Recognition) treating the input character as an image rather than a set of sketched points and performing recognition on the image. The second area is doing sketch based recognition, which takes the input character as a set of points with x, y coordinates or possible a timestamp.
Discussion
In the online character recognition space, the problem is even more complex as we have to process the same input character and give the recognition result within a certain timeframe to support its use in a realtime application. A lot of structural and rule based methods have been explored in this area, some being discussed in previous readings like paper from Rubine or Long. Another type of method applied are statistical methods using sketch as a realtime application of providing more information by giving more strokes and using this information to make a prediction. Markov Models have been used to model this process.
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