Abstract
Barcodes have been long used for data storage. Detecting and locating barcodes in images of complex background is an essential yet challenging step in the process of automatic barcode reading. This work proposed an algorithm that localizes and segments two-dimensional quick response (QR) barcodes. The localization involved a convolutional neural network that could detect partial QR barcodes. Majority voting was then applied to determine barcode locations. Then image processing algorithms were implemented to segment barcodes from the background. Experimental results shows that the proposed approach was robust to detect QR barcodes with rotation and deformation.
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