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EM-Based joint symbol and blur estimation for 2D barcode

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4 Author(s)
Noura Dridi ; Université Lille Nord de France, Institut TELECOM, TELECOM Lille1, LAGIS FRE 3303 CNRS, France ; Yves Delignon ; Wadih Sawaya ; Christelle Garnier

Decoding a severely blurred 2D barcode can be considered as a special case of blind image restoration issue. In this paper, we propose an appropriate system model which includes the original image with the particularities related to barcode, the blur and the observed image. We develop an unsupervised algorithm that jointly estimates the blur and detects the symbols using the maximum likelihood (ML) criterion. Besides, we show that when taking into account the spatial properties of the barcode, the prohibitive complexity of the ML algorithm can be reduced without degrading its performance. Simulation results show that the algorithm performs accurate estimation of the blur and achieves good performance for symbol detection which is close to that obtained with supervised algorithm.

Published in:

Image and Signal Processing and Analysis (ISPA), 2011 7th International Symposium on

Date of Conference:

4-6 Sept. 2011