A symbol-based algorithm for decoding bar codes

TL;DR

This paper introduces a symbol-based decoding algorithm for bar codes that leverages known symbology to improve robustness and accuracy in noisy, uncertain scanning conditions.

Contribution

The paper presents a novel greedy reconstruction algorithm that incorporates bar code symbology directly, reducing problem complexity and enhancing robustness compared to traditional image reconstruction methods.

Findings

Algorithm is robust to noise and parameter uncertainties.

Numerical examples demonstrate high accuracy in reconstruction.

Method significantly outperforms traditional approaches in noisy environments.

Abstract

We investigate the problem of decoding a bar code from a signal measured with a hand-held laser-based scanner. Rather than formulating the inverse problem as one of binary image reconstruction, we instead incorporate the symbology of the bar code into the reconstruction algorithm directly, and search for a sparse representation of the UPC bar code with respect to this known dictionary. Our approach significantly reduces the degrees of freedom in the problem, allowing for accurate reconstruction that is robust to noise and unknown parameters in the scanning device. We propose a greedy reconstruction algorithm and provide robust reconstruction guarantees. Numerical examples illustrate the insensitivity of our symbology-based reconstruction to both imprecise model parameters and noise on the scanned measurements.