Existing barcode signal restoration algorithms are not robust to unmodeled outliers that may exist in scanned barcode images due to scratches, dirts, etc. In this paper, we describe a robust barcode signal restoration algorithm that uses the hybrid L1-L2 norm as a similarity measure. To optimze the similarity measure, we propose a modified iterative reweighted least squares algorithm based on the one step minimization of a quadratic surrogate function. In the simulations and experiments with barcode images, the proposed method showed better robustness than the conventional MSE based method. In addition, the proposed method converged quickly during optimization process.
|Number of pages||6|
|Journal||Transactions of the Korean Institute of Electrical Engineers|
|State||Published - Oct 2007|
- Bar code
- Blind deconvolution
- Iterative re-weighted least squares