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- W1758396985 abstract "This paper deals with a simple and effective set of features for (handprinted) character representation in automatic reading systems. These features, computed within regularly placed windows spanning the character bitmap, consist of a combination of average pixel density and measures of local alignment along some directions. Patterns from different databases call be accommodated by choosing a variable window size. These features used in conjunction with a neural classifier (MLP) yielded a very high accuracy on several handprinted character databases, including NIST's ones. Moreover they are easily implementable in VLSI, with throughputs as high as 250,000 characters/sec." @default.
- W1758396985 created "2016-06-24" @default.
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- W1758396985 date "2002-11-19" @default.
- W1758396985 modified "2023-09-27" @default.
- W1758396985 title "Simple feature extraction for handwritten character recognition" @default.
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- W1758396985 doi "https://doi.org/10.1109/icip.1995.537640" @default.
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