Metal Label Pressed Protuberant Characters Recognition Based on Hidden Markov Model

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Abstract:

A recognition method of pressed protuberant characters based on Hidden Markov models and Neural Network is applied, which the surface curvature properties and the relation of metal label characters are analyzed in detail. The shape index of the characters is extracted. A neural network is used to estimate probabilities for the characters depended on the surface curvature properties, then deriving the best word choice from a sequence of state transition. It is shown in test that the proposed method can be used to recognize the pressed protuberant on metal label.

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667-671

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February 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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