Extraction of data from preprinted forms
Machine Vision and Applications - Special issue: document image analysis techniques
Fractal image compression: theory and application
Fractal image compression: theory and application
A distributed management system for testing document image analysis algorithms
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Adaptive Document Binarization
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Name and Address Block Reader system for tax form processing
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
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This paper describes a new approach for automated quality improvement of grey-scale document images, called STORM. The grey-scale images are first adaptively partitioned into representative regions, whose content is analyzed using a set of document image features developed and adapted for the purpose. The document condition and quality information is evaluated for defect pattern classification in a given entity. This data is then processed using a neural network classifier to expose and priorize the image defects, if any. The evaluation information is further partitioned using the soft control technique by mapping and parametrising the evaluation classes into available image operation techniques. The document type and domain characteristics are used to bias these operations. The experiments cover over 1000 document images in different categories having degradation types in various degree. The outcome shows good results in most of these domains with an automated process.