Abstract:
The problem of word spotting in handwritten archives is approached by matching global shape features. A set of visual templates is used to define the keyword class of interest, and initiate a search for words exhibiting high shape similarity to the model set. Major problems of segmenting cursive script into individual words are avoided by applying line-oriented processing to the document pages. The use of profile-oriented features facilitates the application of dynamic programming techniques to pattern matching, and allows us to achieve high levels of recognition performance. Results of experiments with old Spanish manuscripts show a high recognition rate of the proposed approach.
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Kolcz, A., Alspector, J., Augusteijn, M. et al. A Line-Oriented Approach to Word Spotting in Handwritten Documents. Pattern Analysis & Applications 3, 153–168 (2000). https://doi.org/10.1007/s100440070020
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DOI: https://doi.org/10.1007/s100440070020