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We present a useful method for assessing the quality of a typewritten document image and automatically selecting an optimal restoration method based on that assessment. We use five quality measures that assess the severity of background speckle, touching characters, and broken characters. A linear classifier uses these measures to select a restoration(More)
A system for automatically identifying the script used in a handwritten document image is described. The system was developed using a 496-document dataset representing six scripts, eight languages, and 279 writers. Documents were characterized by the mean, standard deviation, and skew of five connected component features. A linear discriminant analysis was(More)
We describe a system that automatically identifies the script used in documents stored electronically in image form. The system can learn to distinguish any number of scripts. It develops a set of representative symbols (templates) for each script by clustering textual symbols from a set of training documents and representing each cluster by its centroid.(More)
We present a new framework for rapid development of mixed-initiative dialog systems. Using this framework, a developer can author sophisticated dialog systems for multiple channels of interaction by specifying an interaction modality, a rich task hierarchy and task parameters, and domain-specific modules. The framework includes a dialog history that tracks(More)