2 February 2012 Robust recognition of 1D barcodes using Hough transform
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Abstract
In this paper we present an algorithm for the recognition of 1D barcodes using the Hough transform, which is highly robust regarding the typical degraded image. The algorithm addresses various typical image distortions, such as inhomogeneous illumination, reflections, damaged barcode or blurriness etc. Other problems arise from recognizing low quality printing (low contrast or poor ink receptivity). Traditional approaches are unable to provide a fast solution for handling such complex and mixed noise factors. A multi-level method offers a better approach to best manage competing constraints of complex noise and fast decode. At the lowest level, images are processed in gray scale. At the middle level, the image is transformed into the Hough domain. At the top level, global results, including missing information, is processed within a global context including domain heuristics as well as OCR. The three levels work closely together by passing information up and down between levels.
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John Dwinell, John Dwinell, Peng Bian, Peng Bian, Long Xiang Bian, Long Xiang Bian, } "Robust recognition of 1D barcodes using Hough transform", Proc. SPIE 8300, Image Processing: Machine Vision Applications V, 83000K (2 February 2012); doi: 10.1117/12.907598; https://doi.org/10.1117/12.907598
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