Applications of hidden Markov models in bar code decoding

S. Krešić-Jurić; D. Madej; Fadil Santosa

doi:10.1016/j.patrec.2006.03.014

Applications of hidden Markov models in bar code decoding

S. Krešić-Jurić, D. Madej, Fadil Santosa

School of Mathematics

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

We present a novel approach to edge detection in bar code signals using a hidden Markov model (HMM). We also present an algorithm for selection of an optimal filter scale used in smoothing the data. Experimental results show that the proposed HMM is superior in performance compared with existing algorithms in commercial scanners.

Original language	English (US)
Pages (from-to)	1665-1672
Number of pages	8
Journal	Pattern Recognition Letters
Volume	27
Issue number	14
DOIs	https://doi.org/10.1016/j.patrec.2006.03.014
State	Published - Oct 15 2006

Keywords

Bar code decoding
Edge detection
Filter scale selection
Hidden Markov model

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10.1016/j.patrec.2006.03.014

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title = "Applications of hidden Markov models in bar code decoding",

abstract = "We present a novel approach to edge detection in bar code signals using a hidden Markov model (HMM). We also present an algorithm for selection of an optimal filter scale used in smoothing the data. Experimental results show that the proposed HMM is superior in performance compared with existing algorithms in commercial scanners.",

keywords = "Bar code decoding, Edge detection, Filter scale selection, Hidden Markov model",

author = "S. Kre{\v s}i{\'c}-Juri{\'c} and D. Madej and Fadil Santosa",

year = "2006",

month = oct,

day = "15",

doi = "10.1016/j.patrec.2006.03.014",

language = "English (US)",

volume = "27",

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journal = "Pattern Recognition Letters",

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number = "14",

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T1 - Applications of hidden Markov models in bar code decoding

AU - Krešić-Jurić, S.

AU - Madej, D.

AU - Santosa, Fadil

PY - 2006/10/15

Y1 - 2006/10/15

N2 - We present a novel approach to edge detection in bar code signals using a hidden Markov model (HMM). We also present an algorithm for selection of an optimal filter scale used in smoothing the data. Experimental results show that the proposed HMM is superior in performance compared with existing algorithms in commercial scanners.

AB - We present a novel approach to edge detection in bar code signals using a hidden Markov model (HMM). We also present an algorithm for selection of an optimal filter scale used in smoothing the data. Experimental results show that the proposed HMM is superior in performance compared with existing algorithms in commercial scanners.

KW - Bar code decoding

KW - Edge detection

KW - Filter scale selection

KW - Hidden Markov model

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DO - 10.1016/j.patrec.2006.03.014

M3 - Article

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SP - 1665

EP - 1672

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 14

ER -

Applications of hidden Markov models in bar code decoding

Abstract

Keywords

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