Barcode-based calibration of a 1-D blur restoration pipeline

Abstract

In high-speed printed media inspection environments, image restoration pipelines play a critical role in establishing and continually evaluating performance. A key role of such systems is to understand, mitigate (and possibly remove) artifacts introduced by motion blur. An approach is proposed that uses barcodes to help calibrate a one-dimensional blur restoration pipeline. Techniques are demonstrated whereby the structure of barcode markings may be leveraged to estimate motion blur parameters, even under extreme blur conditions or when the barcode is unknown. In addition, a framework for comparing blur estimation procedures based on barcode readability is introduced. These techniques can be applied independently of one another, but together form a set of useful tools for blur restoration pipeline calibration. Within this framework, it is shown that a low-complexity blur estimation strategy demonstrates performance competitive with state-of-the-art approaches in term of speed and accuracy.