Robust 1-D barcode recognition on camera phones and mobile product information display

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Abstract

In this paper we present a robust algorithm for the recognition of 1-D barcodes using camera phones. The recognition algorithm is highly robust regarding the typical image distortions and was tested on a database of barcode images, which covers typical distortions, such as inhomogeneous illumination, reflections, or blurs due to camera movement. We present results from experiments with over 1,000 images from this database using a MATLAB implementation of our algorithm, as well as experiments on the go, where a Symbian C++ implementation running on a camera phone is used to recognize barcodes in daily life situations. The proposed algorithm shows a close to 100% accuracy in real life situations and yields a very good resolution dependent performance on our database, ranging from 90.5% (640 ×480) up to 99.2% (2592 ×1944). The database is freely available for other researchers. Further we shortly present MobilePID, an application for mobile product information display on web-enabled camera phones. MobilePID uses product information services on the internet or locally stored on-device data. © 2010 Springer-Verlag.

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Wachenfeld, S., Terlunen, S., & Jiang, X. (2010). Robust 1-D barcode recognition on camera phones and mobile product information display. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5960 LNCS, pp. 53–69). https://doi.org/10.1007/978-3-642-12349-8_4

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