Title :
Reading handwritten German words in historical documents
Author :
Steinke, K. ; Yuanchen Zhang
Author_Institution :
Univ. of Appl. Sci. & Arts, Hanover, Germany
Abstract :
The research project “Herbar Digital” was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently there are printed labels on the sheets with handwritten annotations. The annotations are written by the determiner or the finder of the plant. They often describe the plant and give information about its name and where it was found. So procedures have to be developed in order to read the most important handwritten words on the sheets. A HMM-approach, a Fourier-approach and a DTW-approach are compared. With a limited number of words a recognition rate of about 95% is obtained by all three methods.
Keywords :
Fourier series; handwriting recognition; handwritten character recognition; hidden Markov models; history; museums; text analysis; word processing; Botanic Museum Berlin; DTW approach; Fourier approach; Germany; HMM approach; Herbar Digital project; dried plant digitization; dynamic time warping; handwritten German word reading; handwritten annotations; historical documents; paper sheets; Estimation; Feature extraction; Handwriting recognition; Hidden Markov models; Time series analysis; Training; DTW; Fourier; HMM; handwriting recognition; writer recognition;
Conference_Titel :
Image and Signal Processing (CISP), 2012 5th International Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-0965-3
DOI :
10.1109/CISP.2012.6469910
