Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Unconstrained handwriting recognition applied to the processing of bank cheques
Unconstrained handwriting recognition applied to the processing of bank cheques
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Independent Components of Characters are 'Strokes'
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Recognition of offline handwritten words and its extension to phrase recognition
Recognition of offline handwritten words and its extension to phrase recognition
A Majority Voting Scheme for Multiresolution Recognition of Handprinted Numerals
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
An approach to offline handwritten Devanagari word segmentation
International Journal of Computer Applications in Technology
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A hidden Markov model (HMM) for recognition of handwritten Devanagari words is proposed. The HMM has the property that its states are not defined a priori, but are determined automatically based on a database of handwritten word images. A handwritten word is assumed to be a string of several stroke primitives. These are in fact the states of the proposed HMM and are found using certain mixture distributions. One HMM is constructed for each word. To classify an unknown word image, its class conditional probability for each HMM is computed. The classification scheme has been tested on a small handwritten Devanagari word database developed recently. The classification accuracy is 87.71% and 82.89% for training and test sets respectively.