A Robust Software Barcode Reader Using the Hough Transform
ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
Barcode Readers using the Camera Device in Mobile Phones
CW '04 Proceedings of the 2004 International Conference on Cyberworlds
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
The QR-code reorganization in illegible snapshots taken by mobile phones
ICCSA '07 Proceedings of the The 2007 International Conference Computational Science and its Applications
Localization and Segmentation of A 2D High Capacity Color Barcode
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
A 2D Barcode Extraction Method Based on Texture Direction Analysis
ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
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ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Fast QR Code Detection in Arbitrarily Acquired Images
SIBGRAPI '11 Proceedings of the 2011 24th SIBGRAPI Conference on Graphics, Patterns and Images
PClines -- Line detection using parallel coordinates
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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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.