A crucial requirement for automatic barcode reading algorithms is real-time processing also on cheap, poorly performing hardware. Moreover, robustness against potential distortions of the processed signals (noise, blur, poor illumination, low resolution etc.) is a desirable property. After a brief introduction on the barcode world, with a view of related mathematical/statistical formulation of the decoding process, we will briefly outline some important open problems with related state-of-the-art research directions for the industrial barcode reading community.

This presentation is part of Minisymposium “MS70 - Innovative Challenging Applications in Imaging Sciences (2 parts)”
organized by: Roberto Mecca (University of Bologna and University of Cambridge) , Giulia Scalet (Dept. Civil Engineering and Architecture, University of Pavia) , Federica Sciacchitano (Dept. Mathematics, University of Genoa) .

Authors:

Francesco Deppieri (DATALOGIC)

Keywords:

bayesian methods, computer vision, image deblurring, image reconstruction, machine learning