Metal Label Pressed Protuberant Characters Recognition Based on Hidden Markov Model

Abstract:

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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.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

667-671

DOI:

10.4028/www.scientific.net/AMR.187.667

Citation:

W. Chen "Metal Label Pressed Protuberant Characters Recognition Based on Hidden Markov Model", Advanced Materials Research, Vol. 187, pp. 667-671, 2011

Online since:

February 2011

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Price:

$35.00

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