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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Machine vision and applications 8 (1995), S. 215-223 
    ISSN: 1432-1769
    Keywords: Handwriting recognition ; Neural networks ; Cursive script ; Hidden Markov models ; Dictionary search
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We present a writer-independent system for online handwriting recognition that can handle a variety of writing styles including cursive script and handprinting. The input to our system contains the pen trajectory information, encoded as a time-ordered sequence of feature vectors. A time-delay neural network is used to estimate a posteriori probabilities for characters in a word. A hidden Markov model segments the word in a way that optimizes the global word score, using a dictionary in the process. A geometrical normalization scheme and a fast but efficient dictionary search are also presented. Trained on 20 k words from 59 writers, using a 25 k-word dictionary, our system reached recognition rates of 89% for characters and 80% for words on test data from a disjoint set of writers.
    Type of Medium: Electronic Resource
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