Can you tell the sequence of widths of the bars in this barcode?
Our algorithm can!
Project Synopsis
Reading barcodes with standard cameras, such as cellphone cameras, enables interesting opportunities for ubiquitous
computing. Unfortunately, current camera-based barcode readers do not work well when the image has low resolution, is
out of focus, or is blurred due to motion. One main reason for this poor performance is that virtually all existing algorithms
perform some sort of binarization, either by gray scale thresholding or by finding the bar edges. We propose a new approach
to barcode reading that never needs to binarize the image. Instead, we use deformable barcode digit models in a maximum
likelihood setting. We show that the particular nature of these models enables efficient integration over the space of deformations. Global optimization over all digits is then performed using dynamic programming.
Publications:
- O. Gallo and R. Manduchi, Reading 1-D Barcodes with Mobile Phones Using Deformable Templates, IEEE PAMI 2011. (pdf) (bibtex)
- O. Gallo and R. Manduchi, Reading Challenging Barcodes with Cameras, IEEE WACV 2009. (pdf) (bibtex)
- O. Gallo and R. Manduchi, Reading 1D Barcodes from Noisy, Blurred, and Highly Compressed Pictures, Technical Report, 2009. (pdf)
Patents:
O. Gallo and R. Manduchi,
Image-based barcode reader, patent pending, 2011.
Additional material:
- NEW: The MatLab code is now available for research purposes upon request! We are only distributing the code for research purposes in non-commercial environments. Please email me at orazio at soe dot ucsc dot edu from the official email address of your institution to request it!
- The WACV presentation with presenter's notes is here.
- The dataset used in the paper is here.
Acknowledgements:
This research was founded by NIH grant 1 R21 EY017003-01A1.
Bibtex:
@article{GalloPAMI10,
    author = {Orazio Gallo and Roberto Manduchi},
    title = {Reading 1-D Barcodes with Mobile Phones Using Deformable Templates},
    journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
    year = {2011},
  }
@article{GalloWACV09,
    title = {Reading Challenging Barcodes with Cameras},
    author = {Gallo, O., and Manduchi, R.},
    journal = {IEEE Workshop on Applications of Computer Vision},
    year = {2009},
    month = {December}
  }