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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