@inproceedings{pub5241,
    abstract = {This paper investigates a part-based recognition
method of handwritten digits. In the proposed method
the global structure of digit patterns is discarded by representing
each pattern by just a set of local feature vectors.
The method is then comprised of two steps. First,
each of J partial patterns of a target pattern is recognized
into one of ten categories (“0”–“9”) by the nearest
neighbor discrimination with a large database of
reference partial patterns. Second, the category of the
target pattern is determined by the majority voting on
the J local recognition results. Despite the pessimistic
expectation, we have reached recognition rates much
higher than 90% for the task of digit recognition.},
    year = {2010},
    title = {Analysis of Local Features for Handwritten Character Recognition},
    booktitle = {Proceedings of the 20th International Conference on Pattern Recognition. International Conference on Pattern Recognition (ICPR-2010), August 23-26, Istanbul, Turkey},
    pages = {1945-1948},
    publisher = {IEEE},
    author = {Seiichi Uchida and Marcus Liwicki}
}