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Reading 1D Barcodes with Mobile Phones Using Deformable Templates
September 2011 (vol. 33 no. 9)
pp. 1834-1843
ASCII Text
x 
 
Orazio Gallo, Roberto Manduchi, "Reading 1D Barcodes with Mobile Phones Using Deformable Templates," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 9, pp. 1834-1843, September, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2010.229,
author = {Orazio Gallo and Roberto Manduchi},
title = {Reading 1D Barcodes with Mobile Phones Using Deformable Templates},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {33},
number = {9},
issn = {0162-8828},
year = {2011},
pages = {1834-1843},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.229},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Reading 1D Barcodes with Mobile Phones Using Deformable Templates
IS - 9
SN - 0162-8828
SP1834
EP1843
EPD - 1834-1843
A1 - Orazio Gallo,
A1 - Roberto Manduchi,
PY - 2011
KW - Barcodes
KW - UPC-A
KW - mobile devices
KW - deformable templates.
VL - 33
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Orazio Gallo, University of California, Santa Cruz, Santa Cruz
Roberto Manduchi, University of California, Santa Cruz, Santa Cruz
Camera cellphones have become ubiquitous, thus opening a plethora of opportunities for mobile vision applications. For instance, they can enable users to access reviews or price comparisons for a product from a picture of its barcode while still in the store. Barcode reading needs to be robust to challenging conditions such as blur, noise, low resolution, or low-quality camera lenses, all of which are extremely common. Surprisingly, even state-of-the-art barcode reading algorithms fail when some of these factors come into play. One reason resides in the early commitment strategy that virtually all existing algorithms adopt: The image is first binarized and then only the binary data are processed. We propose a new approach to barcode decoding that bypasses binarization. Our technique relies on deformable templates and exploits all of the gray-level information of each pixel. Due to our parameterization of these templates, we can efficiently perform maximum likelihood estimation independently on each digit and enforce spatial coherence in a subsequent step. We show by way of experiments on challenging UPC-A barcode images from five different databases that our approach outperforms competing algorithms. Implemented on a Nokia N95 phone, our algorithm can localize and decode a barcode on a VGA image (640 \times 480, JPEG compressed) in an average time of 400-500 ms.

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Index Terms:
Barcodes, UPC-A, mobile devices, deformable templates.
Citation:
Orazio Gallo, Roberto Manduchi, "Reading 1D Barcodes with Mobile Phones Using Deformable Templates," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 9, pp. 1834-1843, Sept. 2011, doi:10.1109/TPAMI.2010.229
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