Xerox Corporation

Gilbert B Porter, Iii

Zhigang Fan

Frederick J Roberts, Jr

Mirelsa Fontanes-Pérez

William Soon Hock Tay

A method of detecting the encoding utilized in an electronic document includes testing the text strings to determine whether the electronic document contains only text strings having legal numeric codes. A statistical analysis of the text strings is then conducted to provide a mapping of legally coded candidates. The legally coded candidates are ranked and combined with an expected ranking of legally coded candidates to provide a most probable character mapping.

Automatic detection of character encoding format using statistical analysis of the text strings

A neural network based improving the performance of an omni-font classifier by using recognized characters for additional training is presented. The invention applies the outputs of the hidden layer nodes of the neural net as the feature vector. Characters that are recognized with high confidence are used to dynamically train a secondary classifier. After the secondary classifier is trained, it is combined with the original main classifier. The invention can re-adjust the partition or boundary of feature space, based on on-line learning, by utilizing the secondary classifier data to form an alternative partition location. The new partition can be referred to when a character conflict exists during character recognition.

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Rochester, NY, United States of America

Gilbert B Porter, Iii