Writer Identification Using Text Line Based Features
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A writer identification and verification system
Pattern Recognition Letters
An information extraction system from patient historical documents
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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About 3.5 million dried plants on paper sheets are deposited in the Botanical Museum Berlin in Germany. Frequently they have handwritten annotations (see figure 1). So a procedure had to be developed in order to process the handwriting on the sheet. In the present work an approach tries to identify the writer by handwritten words and to read handwritten keywords. Therefore the word is cut out and transformed into a 6-dimensional time series and compared e.g. by means of DTW-method. A recognition rate of 98.6% is achieved with 12 different words (1200 samples). All herbar documents contain several printed tokens which indicate more information about the plant. With the token it is possible to get information who has found this plant, where this plant was found (country and sometimes the town), what kind of plant it is and so on. By using the local connections of the text it is possible to get more information from the herbar document, e.g. to find and recognize handwritten text in a defined area.