DocumentCode
2002262
Title
Blind Detection of Severely Blurred 1D Barcode
Author
Dridi, Noura ; Delignon, Yves ; Sawaya, Wadih ; Septier, François
Author_Institution
Inst. TELECOM, Univ. Lille Nord de France, Villeneuve-d´´Ascq, France
fYear
2010
fDate
6-10 Dec. 2010
Firstpage
1
Lastpage
5
Abstract
In this paper, we present a joint blind channel estimation and symbol detection for decoding a blurred and noisy 1D barcode captured image. From an information transmission point of view, we show that the channel impulse response, the noise power and the symbols can be efficiently estimated by taking into account the signal structure such as the cyclostationary property of the hidden Markov process to estimate. Based on the Expectation-Maximisation method, we show that the new algorithm offers significative performance gain compared to classical ones pushing back the frontiers of the barcode technology.
Keywords
channel estimation; expectation-maximisation algorithm; hidden Markov models; image denoising; image restoration; blind detection; channel impulse response; expectation-maximisation method; hidden Markov process; joint blind channel estimation; noisy 1D barcode captured image decoding; severely blurred 1D barcode; symbol detection; Channel estimation; Equations; Estimation; Hidden Markov models; Joints; Mathematical model; Noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Telecommunications Conference (GLOBECOM 2010), 2010 IEEE
Conference_Location
Miami, FL
ISSN
1930-529X
Print_ISBN
978-1-4244-5636-9
Electronic_ISBN
1930-529X
Type
conf
DOI
10.1109/GLOCOM.2010.5684145
Filename
5684145
Link To Document