Document Image Enhancement

"We will develop a framework for associating measurements of document image characteristics with image transformation techniques and evaluating the utility of both using a supervised machine learning component of the framework. From a training set of imagesdescribed in terms of their characteristic values, each with its best transformation method, this component will learn a function that maps combinations of feature values to single best image transformation methods. This research extends the ideas in workby McNamara, Casey, Smith, and Bradburn (1996) and by Cannon, Hochberg, and Kelly (1999).In Phase I, we will develop an application that includes components for: calculating image feature values or quality measures, applying image transformation methods, training the system to associate profiles of image characteristics with imagetransformation methods, selecting image transformation methods on the basis of this training, evaluating OCR results against available ground truth, and evaluating human readability. Because this phase is centered on development of a complete framework,the initial set of characteristics will have a single measure, and likewise the initial set of transformation techniques will include one method (other than keeping the original image). In the Phase I Option, we will add an additional image characteristicand transformation technique. Anticipated benefits of this research and development will be realized in