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SCCG 2012

Fast detection and recognition of QR codes in high-resolution images

Szentandrasi, I., Herout, A. and Dubska, M., Graph@FIT, Brno University of Technology
Corresponding author email: iszentandrasi[at]fit.vutbr.cz

Abstract

This paper deals with detection and recognition of matrix codes, such as the QR codes, in high-resolution images of real-world scenes. The goal is to provide a detector capable of operation in real time even on high-resolution images (several megapixels). We present an efficient algorithm for detection of possible occurrences of the codes. This algorithm is characterized by a very low false negative rate and a reasonable false alarm rate. The results of our algorithm are to be followed by an accurate detection/recognition algorithm. We propose to use a recent matrix code detection and recognition algorithm based on Hough transform, because it can reuse some information computed by our new pre-detection algorithm and thus a further reduce of computational demands can be achieved. Since there are no publicly available annotated datasets for evaluation of this kind of algorithm, we collected a number of images and annotated them; these images will be made publicly available to allow for a proper comparison. Our algorithm was evaluated on this dataset and the results are reported in the paper.

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[full paper], [cite]

Image dataset: [qrcode-datasets.zip]

Citation

@INPROCEEDINGS{QRcodes-SCCG-2012 author = {Szentandr\'{a}si, Istv\'{a}n and Herout, Adam and Dubsk\'{a}, Mark{\'e}ta}, title = {Fast Detection and Recognition of QR Codes in High-resolution Images}, booktitle = {Proceedings of the 28th Spring Conference on Computer Graphics}, series = {SCCG '12}, year = {2012}, isbn = {978-1-4503-1977-5}, location = {Budmerice, Slovakia}, pages = {129--136}, numpages = {8}, url = {http://doi.acm.org/10.1145/2448531.2448548}, doi = {10.1145/2448531.2448548}, acmid = {2448548}, publisher = {ACM}, address = {New York, NY, USA}, }

Examples of Results

Acknowledgements

This research was supported by the research project CEZMSMT, MSM0021630528, by the CEZMSMT project IT4I - CZ 1.05/1.1.00/02.0070, and by the BUT grant FIT-S-11-2.
(c) 2014, Marketa Dubska